Using Head Movement to Recognize Activity. - Anant Madabhushi; J. K. Aggarwal (ICPR, 2000)

Automatic boundary extraction of ultrasonic breast lesions. - Anant Madabhushi; Dimitris N. Metaxas (ISBI, 2002)

Automatic quantification of liver-heart cross-talk for quality assessment in SPECT myocardial perfusion imaging. - Guo-Qing Wei; Anant Madabhushi; Jian Zhong Qian; John C. Engdahl (Image Processing, 2002)

A Novel Stochastic Combination of 3D Texture Features for Automated Segmentation of Prostatic Adenocarcinoma from High Resolution MRI. - Anant Madabhushi; Michael D. Feldman; Dimitris N. Metaxas; Deborah Chute; John Tomaszewski 001 (MICCAI (1), 2003)

The interplay between intensity standardization and field inhomogeneity correction in MR image processing. - Anant Madabhushi; Jayaram K. Udupa (Image Processing, 2003)

Combining Low, High-Level and Empirical Domain Specific Knowledge for Automated Segmentation of Ultrasonic Breast Lesions. - Anant Madabhushi; Dimitris N. Metaxas (IEEE Trans. Medical Imaging, 2003)

Graph Embedding to Improve Supervised Classification and Novel Class Detection: Application to Prostate Cancer. - Anant Madabhushi; Jianbo Shi; Mark Rosen; John Tomaszewski 001; Michael D. Feldman (MICCAI, 2005)

New methods of MR image intensity standardization via generalized scale. - Anant Madabhushi; Jayaram K. Udupa (Image Processing, 2005)

Generalized ball-scale: theory, algorithms, and application to image inhomogeneity correction. - Anant Madabhushi; Jayaram K. Udupa; Andre D. A. Souza (Image Processing, 2005)

Generalized scale-based image filtering. - Andre D. A. Souza; Jayaram K. Udupa; Anant Madabhushi (Image Processing, 2005)

Automated detection of prostatic adenocarcinoma from high-resolution ex vivo MRI. - Anant Madabhushi; Michael D. Feldman; Dimitris N. Metaxas; John Tomaszewski 001; Deborah Chute (IEEE Trans. Medical Imaging, 2005)

Interplay between intensity standardization and inhomogeneity correction in MR image processing. - Anant Madabhushi; Jayaram K. Udupa (IEEE Trans. Medical Imaging, 2005)

Comparing Ensembles of Learners: Detecting Prostate Cancer from High Resolution MRI. - Anant Madabhushi; Jianbo Shi; Michael D. Feldman; Mark Rosen; John Tomaszewski 001 (CVAMIA, 2006)

Detecting Prostatic Adenocarcinoma From Digitized Histology Using a Multi-Scale Hierarchical Classification Approach. - Scott Doyle; Carlos Rodriguez; Anant Madabhushi; John Tomaszewski 001; Michael D. Feldman (EMBC, 2006)

Distinguishing Lesions from Posterior Acoustic Shadowing in Breast Ultrasound via Non-Linear Dimensionality Reduction. - Anant Madabhushi; Peng Yang; Mark Rosen; Susan Weinstein (EMBC, 2006)

Breast Cancer Diagnosis Using Neural-Based Linear Fusion Strategies. - Yunfeng Wu; Cong Wang; Sin Chun Ng; Anant Madabhushi; Yixin Zhong (ICONIP (3), 2006)

A Boosting Cascade for Automated Detection of Prostate Cancer from Digitized Histology. - Scott Doyle; Anant Madabhushi; Michael D. Feldman; John Tomaszewski 001 (MICCAI (2), 2006)

Generalized scale: Theory, algorithms, and application to image inhomogeneity correction. - Anant Madabhushi; Jayaram K. Udupa; Andre D. A. Souza (Comput. Vis. Image Underst., 2006)

A Combined Feature Ensemble Based Mutual Information Scheme for Robust Inter-Modal, Inter-Protocol Image Registration. - Jonathan Chappelow; Anant Madabhushi; Mark Rosen; John Tomaszewski 001; Michael D. Feldman (ISBI, 2007)

Automated Grading of Prostate Cancer Using Architectural and Textural Image Features. - Scott Doyle; Mark I. Hwang; Kinsuk Shah; Anant Madabhushi; Michael D. Feldman; John Tomaszewski 001 (ISBI, 2007)

An Empirical Comparison of Dimensionality Reduction Methods for Classifying Gene and Protein Expression Datasets. - George Lee 002; Carlos Rodriguez; Anant Madabhushi (ISBRA, 2007)

A Hierarchical Unsupervised Spectral Clustering Scheme for Detection of Prostate Cancer from Magnetic Resonance Spectroscopy (MRS). - Pallavi Tiwari; Anant Madabhushi; Mark Rosen (MICCAI (2), 2007)

Multimodal image registration of ex vivo 4 Tesla MRI with whole mount histology for prostate cancer detection. - Jonathan Chappelow; Anant Madabhushi; Mark Rosen; John Tomaszewski 001; Michael D. Feldman (Image Processing, 2007)

Automated grading of breast cancer histopathology using spectral clusteringwith textural and architectural image features. - Scott Doyle; Shannon Agner; Anant Madabhushi; Michael D. Feldman; John Tomaszewski 001 (ISBI, 2008)

Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology. - Shivang Naik; Scott Doyle; Shannon Agner; Anant Madabhushi; Michael D. Feldman; John Tomaszewski 001 (ISBI, 2008)

Novel kinetic texture features for breast lesion classification on dynamic contrast enhanced (DCE) MRI. - Shannon C. Agner; Salil Soman; Edward Libfeld; Margie McDonald; Mark A. Rosen; Mitchell D. Schnall; Deanna Chin; John L. Nosher; Anant Madabhushi (Computer-Aided Diagnosis, 2008)

Improving supervised classification accuracy using non-rigid multimodal image registration: detecting prostate cancer. - Jonathan Chappelow; Satish Viswanath; James Monaco; Mark Rosen; John Tomaszewski 001; Michael D. Feldman; Anant Madabhushi (Computer-Aided Diagnosis, 2008)

A consensus embedding approach for segmentation of high resolution in vivo prostate magnetic resonance imagery. - Satish Viswanath; Mark Rosen; Anant Madabhushi (Computer-Aided Diagnosis, 2008)

A meta-classifier for detecting prostate cancer by quantitative integration of in vivo magnetic resonance spectroscopy and magnetic resonance imaging. - Satish Viswanath; Pallavi Tiwari; Mark Rosen; Anant Madabhushi (Computer-Aided Diagnosis, 2008)

Consensus-Locally Linear Embedding (C-LLE): Application to Prostate Cancer Detection on Magnetic Resonance Spectroscopy. - Pallavi Tiwari; Mark Rosen; Anant Madabhushi (MICCAI (2), 2008)

Multi-Attribute Non-initializing Texture Reconstruction Based Active Shape Model (MANTRA). - Robert Toth; Jonathan Chappelow; Mark Rosen; Sona Pungavkar; Arjun Kalyanpur; Anant Madabhushi (MICCAI (1), 2008)

A Comprehensive Segmentation, Registration, and Cancer Detection Scheme on 3 Tesla In VivoProstate DCE-MRI. - Satish Viswanath; B. Nicolas Bloch; Elizabeth Genega; Neil Rofsky; Robert E. Lenkinski; Jonathan Chappelow; Robert Toth; Anant Madabhushi (MICCAI (1), 2008)

A multi-modal prostate segmentation scheme by combining spectral clustering and active shape models. - Robert Toth; Pallavi Tiwari; Mark Rosen; Arjun Kalyanpur; Sona Pungavkar; Anant Madabhushi (Image Processing, 2008)

Image filtering via generalized scale. - Andre D. A. Souza; Jayaram K. Udupa; Anant Madabhushi (Medical Image Anal., 2008)

Investigating the Efficacy of Nonlinear Dimensionality Reduction Schemes in Classifying Gene and Protein Expression Studies. - George Lee 002; Carlos Rodriguez; Anant Madabhushi (IEEE ACM Trans. Comput. Biol. Bioinform., 2008)

Classifying Ayurvedic Pulse Signals Via Consensus Locally Linear Embedding. - Amod Jog; Aniruddha J. Joshi; Sharat Chandran; Anant Madabhushi (BIOSIGNALS, 2009)

Segmentation and Classification of Triple Negative Breast Cancers Using DCE-MRI. - Shannon Agner; Jun Xu 005; Hussain Fatakdawala; Shridar Ganesan; Anant Madabhushi; Sarah Englander; Mark Rosen; Kathleen Thomas; Mitchell D. Schnall; Michael D. Feldman; John Tomaszewski 001 (ISBI, 2009)

Computer-Aided Prognosis of ER+ Breast Cancer Histopathology and Correlating Survival Outcome with Oncotype DX Assay. - Ajay Basavanhally; Jun Xu 005; Shridar Ganesan; Anant Madabhushi (ISBI, 2009)

A Knowledge Representation Framework for Integration, Classification of Multi-Scale Imaging and Non-Imaging Data: Preliminary Results in Predicting Prostate Cancer Recurrence by Fusing Mass Spectrometry and Histology. - George Lee 002; Scott Doyle; James Monaco; Michael D. Feldman; Stephen R. Master; John Tomaszewski 001; Anant Madabhushi (ISBI, 2009)

A boosted distance metric: application to content based image retrieval and classification of digitized histopathology. - Jay Naik; Scott Doyle; Ajay Basavanhally; Shridar Ganesan; Michael D. Feldman; John Tomaszewski 001; Anant Madabhushi (Computer-Aided Diagnosis, 2009)

Integrating structural and functional imaging for computer assisted detection of prostate cancer on multi-protocol in vivo 3 Tesla MRI. - Satish Viswanath; B. Nicolas Bloch; Mark Rosen; Jonathan Chappelow; Robert Toth; Neil Rofsky; Robert E. Lenkinski; Elizabeth Genega; Arjun Kalyanpur; Anant Madabhushi (Computer-Aided Diagnosis, 2009)

Hierarchical Normalized Cuts: Unsupervised Segmentation of Vascular Biomarkers from Ovarian Cancer Tissue Microarrays. - Andrew Janowczyk; Sharat Chandran; Rajendra Singh; Dimitra Sasaroli; George Coukos; Michael D. Feldman; Anant Madabhushi (MICCAI (1), 2009)

Spectral Embedding Based Probabilistic Boosting Tree (ScEPTre): Classifying High Dimensional Heterogeneous Biomedical Data. - Pallavi Tiwari; Mark Rosen; Galen Reed; John Kurhanewicz; Anant Madabhushi (MICCAI (1), 2009)

COLLINARUS: collection of image-derived non-linear attributes for registration using splines. - Jonathan Chappelow; B. Nicolas Bloch; Neil Rofsky; Elizabeth Genega; Robert E. Lenkinski; William DeWolf; Satish Viswanath; Anant Madabhushi (Image Processing, 2009)

Probabilistic pairwise Markov models: application to prostate cancer detection. - James Monaco; John Tomaszewski 001; Michael D. Feldman; Mehdi Moradi; Parvin Mousavi; Alexander Boag; Chris Davidson; Purang Abolmaesumi; Anant Madabhushi (Image Processing, 2009)

WERITAS: weighted ensemble of regional image textures for ASM segmentation. - Robert Toth; Scott Doyle; Mark Rosen; Arjun Kalyanpur; Sona Pungavkar; B. Nicolas Bloch; Elizabeth Genega; Neil Rofsky; Robert E. Lenkinski; Anant Madabhushi (Image Processing, 2009)

Pattern Recognition in Histopathological Images: An ICPR 2010 Contest. - Metin N. Gurcan; Anant Madabhushi; Nasir M. Rajpoot (ICPR Contests, 2010)

Predicting classifier performance with a small training set: applications to computer-aided diagnosis and prognosis. - Ajay Basavanhally; Scott Doyle; Anant Madabhushi (ISBI, 2010)

Multi-attribute combined mutual information (MACMI): an image registration framework for leveraging multiple data channels. - Jonathan Chappelow; Anant Madabhushi (ISBI, 2010)

Evaluation of effects of jpeg2000 compression on a computer-aided detection system for prostate cancer on digitized histopathology. - Scott Doyle; James Monaco; Anant Madabhushi; Stefan Lindholm; Patric Ljung; Lance Ladic; John Tomaszewski 001; Michael D. Feldman (ISBI, 2010)

Computer-aided prognosis: predicting patient and disease outcome via multi-modal image analysis. - Anant Madabhushi; Ajay Basavanhally; Scott Doyle; Shannon Agner; George Lee 002 (ISBI, 2010)

An integrated framework for analyzing three-dimensional shape differences: evaluating prostate morphometry. - Rachel Sparks; Robert Toth; Jonathan Chappelow; Gaoyu Xiao; Anant Madabhushi (ISBI, 2010)

Novel Morphometric Based Classification via Diffeomorphic Based Shape Representation Using Manifold Learning. - Rachel Sparks; Anant Madabhushi (MICCAI (3), 2010)

Semi Supervised Multi Kernel (SeSMiK) Graph Embedding: Identifying Aggressive Prostate Cancer via Magnetic Resonance Imaging and Spectroscopy. - Pallavi Tiwari; John Kurhanewicz; Mark Rosen; Anant Madabhushi (MICCAI (3), 2010)

Markov Random Field driven Region-Based Active Contour Model (MaRACel): Application to Medical Image Segmentation. - Jun Xu 005; James Monaco; Anant Madabhushi (MICCAI (3), 2010)

High-Throughput Prostate Cancer Gland Detection, Segmentation, and Classification from Digitized Needle Core Biopsies. - Jun Xu 005; Rachel Sparks; Andrew Janowczyk; John Tomaszewski 001; Michael D. Feldman; Anant Madabhushi (Prostate Cancer Imaging, 2010)

Computer-assisted targeted therapy (CATT) for prostate radiotherapy planning by fusion of CT and MRI. - Jonathan Chappelow; Stefan Both; Satish Viswanath; Stephen Hahn 002; Michael D. Feldman; Mark Rosen; John Tomaszewski 001; Neha Vapiwala; Pratik Patel; Anant Madabhushi (Image-Guided Procedures, 2010)

A weighted mean shift, normalized cuts initialized color gradient based geodesic active contour model: applications to histopathology image segmentation. - Jun Xu 005; Andrew Janowczyk; Sharat Chandran; Anant Madabhushi (Image Processing, 2010)

A structural-functional MRI-based disease atlas: application to computer-aided-diagnosis of prostate cancer. - Gaoyu Xiao; B. Nicolas Bloch; Jonathan Chappelow; Elizabeth Genega; Neil Rofsky; Robert E. Lenkinski; Anant Madabhushi (Image Processing, 2010)

Consensus of Ambiguity: Theory and Application of Active Learning for Biomedical Image Analysis. - Scott Doyle; Anant Madabhushi (PRIB, 2010)

Semi-Supervised Graph Embedding Scheme with Active Learning (SSGEAL): Classifying High Dimensional Biomedical Data. - George Lee 002; Anant Madabhushi (PRIB, 2010)

High-throughput detection of prostate cancer in histological sections using probabilistic pairwise Markov models. - James Monaco; John Tomaszewski 001; Michael D. Feldman; Ian S. Hagemann; Mehdi Moradi; Parvin Mousavi; Alexander Boag; Chris Davidson; Purang Abolmaesumi; Anant Madabhushi (Medical Image Anal., 2010)

Computerized Image-Based Detection and Grading of Lymphocytic Infiltration in HER2+ Breast Cancer Histopathology. - Ajay Basavanhally; Shridar Ganesan; Shannon Agner; James Monaco; Michael D. Feldman; John Tomaszewski 001; Gyan Bhanot; Anant Madabhushi (IEEE Trans. Biomed. Eng., 2010)

Expectation-Maximization-Driven Geodesic Active Contour With Overlap Resolution (EMaGACOR): Application to Lymphocyte Segmentation on Breast Cancer Histopathology. - Hussain Fatakdawala; Jun Xu 005; Ajay Basavanhally; Gyan Bhanot; Shridar Ganesan; Michael D. Feldman; John Tomaszewski 001; Anant Madabhushi (IEEE Trans. Biomed. Eng., 2010)

An integrated texton and bag of words classifier for identifying anaplastic medulloblastomas. - Joseph Galaro; Alexander R. Judkins; David Ellison; Jennifer Baccon; Anant Madabhushi (EMBC, 2011)

Evaluating feature selection strategies for high dimensional, small sample size datasets. - Abhishek Golugula; George Lee 002; Anant Madabhushi (EMBC, 2011)

Supervised regularized canonical correlation analysis: Integrating histologic and proteomic data for predicting biochemical failures. - Abhishek Golugula; George Lee 002; Stephen R. Master; Michael D. Feldman; John Tomaszewski 001; Anant Madabhushi (EMBC, 2011)

Interplay between bias field correction, intensity standardization, and noise filtering for T2-weighted MRI. - Daniel Palumbo; Brian Yee; Patrick O'Dea; Shane Leedy; Satish Viswanath; Anant Madabhushi (EMBC, 2011)

Spatially weighted mutual information (SWMI) for registration of digitally reconstructed ex vivo whole mount histology and in vivo prostate MRI. - Pratik Patel; Jonathan Chappelow; John Tomaszewski 001; Michael D. Feldman; Mark Rosen; Natalie Shih; Anant Madabhushi (EMBC, 2011)

Detection of prostate cancer on histopathology using color fractals and Probabilistic Pairwise Markov models. - Elaine Yu; James P. Monaco; John Tomaszewski 001; Natalie Shih; Michael D. Feldman; Anant Madabhushi (EMBC, 2011)

Active Contour for Overlap Resolution using Watershed BASED initialization (ACOReW): Applications to histopathology. - Sahirzeeshan Ali; Anant Madabhushi (ISBI, 2011)

A boosted classifier for integrating multiple fields of view: Breast cancer grading in histopathology. - Ajay Basavanhally; Shridar Ganesan; Natalie Shih; Carolyn Mies; Michael D. Feldman; John Tomaszewski 001; Anant Madabhushi (ISBI, 2011)

Cascaded multi-class pairwise classifier (CascaMPa) for normal, cancerous, and cancer confounder classes in prostate histology. - Scott Doyle; Michael D. Feldman; John Tomaszewski 001; Natalie Shih; Anant Madabhushi (ISBI, 2011)

Out-of-sample extrapolation using semi-supervised manifold learning (OSE-SSL): Content-based image retrieval for prostate histology grading. - Rachel Sparks; Anant Madabhushi (ISBI, 2011)

Boosted Spectral Embedding (BoSE): Applications to content-based image retrieval of histopathology. - Akshay Sridhar; Scott Doyle; Anant Madabhushi (ISBI, 2011)

Multi-modal data fusion schemes for integrated classification of imaging and non-imaging biomedical data. - Pallavi Tiwari; Satish Viswanath; George Lee 002; Anant Madabhushi (ISBI, 2011)

Medial axis based statistical shape model (MASSM): Applications to 3D prostate segmentation on MRI. - Robert Toth; Rachel Sparks; Anant Madabhushi (ISBI, 2011)

CADOnc ©: An integrated toolkit for evaluating radiation therapy related changes in the prostate using multiparametric MRI. - Satish Viswanath; Pallavi Tiwari; Jonathan Chappelow; Robert Toth; John Kurhanewicz; Anant Madabhushi (ISBI, 2011)

Spectral embedding based active contour (SEAC): application to breast lesion segmentation on DCE-MRI. - Shannon Agner; Jun Xu 005; Mark Rosen; Sudha Karthigeyan; Sarah Englander; Anant Madabhushi (Computer-Aided Diagnosis, 2011)

Incorporating domain knowledge for tubule detection in breast histopathology using O'Callaghan neighborhoods. - Ajay Basavanhally; Elaine Yu; Jun Xu 005; Shridar Ganesan; Michael D. Feldman; John Tomaszewski 001; Anant Madabhushi (Computer-Aided Diagnosis, 2011)

Linked statistical shape models for multi-modal segmentation: application to prostate CT-MR segmentation in radiotherapy planning. - Najeeb Chowdhury; Jonathan Chappelow; Robert Toth; Sung Kim; Stephen Hahn 002; Neha Vapiwala; Haibo Lin; Stefan Both; Anant Madabhushi (Computer-Aided Diagnosis, 2011)

Enhanced multi-protocol analysis via intelligent supervised embedding (EMPrAvISE): detecting prostate cancer on multi-parametric MRI. - Satish Viswanath; B. Nicolas Bloch; Jonathan Chappelow; Pratik Patel; Neil Rofsky; Robert E. Lenkinski; Elizabeth Genega; Anant Madabhushi (Computer-Aided Diagnosis, 2011)

Empirical evaluation of bias field correction algorithms for computer-aided detection of prostate cancer on T2w MRI. - Satish Viswanath; Daniel Palumbo; Jonathan Chappelow; Pratik Patel; B. Nicolas Bloch; Neil Rofsky; Robert E. Lenkinski; Elizabeth Genega; Anant Madabhushi (Computer-Aided Diagnosis, 2011)

Adaptive Energy Selective Active Contour with Shape Priors for Nuclear Segmentation and Gleason Grading of Prostate Cancer. - Sahirzeeshan Ali; Robert Veltri; Jonathan I. Epstein; Christhunesa Christudass; Anant Madabhushi (MICCAI (1), 2011)

Variable Ranking with PCA: Finding Multiparametric MR Imaging Markers for Prostate Cancer Diagnosis and Grading. - Shoshana Ginsburg; Pallavi Tiwari; John Kurhanewicz; Anant Madabhushi (Prostate Cancer Imaging, 2011)

Weighted Combination of Multi-Parametric MR Imaging Markers for Evaluating Radiation Therapy Related Changes in the Prostate. - Pallavi Tiwari; Satish Viswanath; John Kurhanewicz; Anant Madabhushi (Prostate Cancer Imaging, 2011)

Aggregated Distance Metric Learning (ADM) for Image Classification in Presence of Limited Training Data. - Gaoyu Xiao; Anant Madabhushi (MICCAI (3), 2011)

Segmenting multiple overlapping objects via a hybrid active contour model incorporating shape priors: applications to digital pathology. - Sahirzeeshan Ali; Anant Madabhushi (Image Processing, 2011)

Local morphologic scale: application to segmenting tumor infiltrating lymphocytes in ovarian cancer TMAs. - Andrew Janowczyk; Sharat Chandran; Michael D. Feldman; Anant Madabhushi (Image Processing, 2011)

Content-based image retrieval utilizing explicit shape descriptors: applications to breast MRI and prostate histopathology. - Rachel Sparks; Anant Madabhushi (Image Processing, 2011)

Integrating an adaptive region-based appearance model with a landmark-free statistical shape model: application to prostate MRI segmentation. - Robert Toth; Julie Bulman; Amish D. Patel; B. Nicolas Bloch; Elizabeth Genega; Neil Rofsky; Robert E. Lenkinski; Anant Madabhushi (Image Processing, 2011)

An Active Learning Based Classification Strategy for the Minority Class Problem: Application to Histopathology Annotation. - Scott Doyle; James Monaco; Michael D. Feldman; John Tomaszewski 001; Anant Madabhushi (BMC Bioinform., 2011)

Supervised Regularized Canonical Correlation Analysis: integrating histologic and proteomic measurements for predicting biochemical recurrence following prostate surgery. - Abhishek Golugula; George Lee 002; Stephen R. Master; Michael D. Feldman; John Tomaszewski 001; David W. Speicher; Anant Madabhushi (BMC Bioinform., 2011)

HistoStitcher©: An interactive program for accurate and rapid reconstruction of digitized whole histological sections from tissue fragments. - Jonathan Chappelow; John Tomaszewski 001; Michael D. Feldman; Natalie Shih; Anant Madabhushi (Comput. Medical Imaging Graph., 2011)

Computer-aided prognosis: Predicting patient and disease outcome via quantitative fusion of multi-scale, multi-modal data. - Anant Madabhushi; Shannon Agner; Ajay Basavanhally; Scott Doyle; George Lee 002 (Comput. Medical Imaging Graph., 2011)

Determining histology-MRI slice correspondences for defining MRI-based disease signatures of prostate cancer. - Gaoyu Xiao; B. Nicolas Bloch; Jonathan Chappelow; Elizabeth Genega; Neil Rofsky; Robert E. Lenkinski; John Tomaszewski 001; Michael D. Feldman; Mark Rosen; Anant Madabhushi (Comput. Medical Imaging Graph., 2011)

Textural Kinetics: A Novel Dynamic Contrast-Enhanced (DCE)-MRI Feature for Breast Lesion Classification. - Shannon Agner; Salil Soman; Edward Libfeld; Margie McDonald; Kathleen Thomas; Sarah Englander; Mark A. Rosen; Deanna Chin; John L. Nosher; Anant Madabhushi (J. Digit. Imaging, 2011)

A magnetic resonance spectroscopy driven initialization scheme for active shape model based prostate segmentation. - Robert Toth; Pallavi Tiwari; Mark Rosen; Galen Reed; John Kurhanewicz; Arjun Kalyanpur; Sona Pungavkar; Anant Madabhushi (Medical Image Anal., 2011)

A high-throughput active contour scheme for segmentation of histopathological imagery. - Jun Xu 005; Andrew Janowczyk; Sharat Chandran; Anant Madabhushi (Medical Image Anal., 2011)

Weighted Maximum Posterior Marginals for Random Fields Using an Ensemble of Conditional Densities From Multiple Markov Chain Monte Carlo Simulations. - James Monaco; Anant Madabhushi (IEEE Trans. Medical Imaging, 2011)

Image segmentation with implicit color standardization using cascaded EM: Detection of myelodysplastic syndromes. - James Monaco; Philipp W. Raess; Ronak Chawla; Adam Bagg; Mitchell Weiss; John Choi; Anant Madabhushi (ISBI, 2012)

Gleason grading of prostate histology utilizing manifold regularization via statistical shape model of manifolds. - Rachel Sparks; Anant Madabhushi (Computer-Aided Diagnosis, 2012)

Incorporating the whole-mount prostate histology reconstruction program Histostitcher into the extensible imaging platform (XIP) framework. - Robert Toth; Jonathan Chappelow; Christoph Vetter; Oliver Kutter; Christoph Russ; Michael D. Feldman; John Tomaszewski 001; Natalie Shih; Anant Madabhushi (Computer-Aided Diagnosis, 2012)

A Visual Latent Semantic Approach for Automatic Analysis and Interpretation of Anaplastic Medulloblastoma Virtual Slides. - Angel Cruz-Roa; Fabio A. González 001; Joseph Galaro; Alexander R. Judkins; David Ellison; Jennifer Baccon; Anant Madabhushi; Eduardo Romero 001 (MICCAI (1), 2012)

Image Segmentation with Implicit Color Standardization Using Spatially Constrained Expectation Maximization: Detection of Nuclei. - James Monaco; Jennifer A. Hipp; D. Lucas; S. Smith; Ulysses J. Balis; Anant Madabhushi (MICCAI (1), 2012)

Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer. - Scott Doyle; Michael D. Feldman; Natalie Shih; John Tomaszewski 001; Anant Madabhushi (BMC Bioinform., 2012)

Consensus embedding: theory, algorithms and application to segmentation and classification of biomedical data. - Satish Viswanath; Anant Madabhushi (BMC Bioinform., 2012)

Class-specific weighting for Markov random field estimation: Application to medical image segmentation. - James Monaco; Anant Madabhushi (Medical Image Anal., 2012)

Editorial: TBME Letters Special Section on Multiscale Biomedical Signal and Image Modeling and Analysis. - Sergio Cerutti; Anant Madabhushi; Shishir K. Shah; Ki H. Chon (IEEE Trans. Biomed. Eng., 2012)

A Boosted Bayesian Multiresolution Classifier for Prostate Cancer Detection From Digitized Needle Biopsies. - Scott Doyle; Michael D. Feldman; John Tomaszewski 001; Anant Madabhushi (IEEE Trans. Biomed. Eng., 2012)

High-Throughput Biomarker Segmentation on Ovarian Cancer Tissue Microarrays via Hierarchical Normalized Cuts. - Andrew Janowczyk; Sharat Chandran; Rajendra Singh; Dimitra Sasaroli; George Coukos; Michael D. Feldman; Anant Madabhushi (IEEE Trans. Biomed. Eng., 2012)

An Integrated Region-, Boundary-, Shape-Based Active Contour for Multiple Object Overlap Resolution in Histological Imagery. - Sahirzeeshan Ali; Anant Madabhushi (IEEE Trans. Medical Imaging, 2012)

Multifeature Landmark-Free Active Appearance Models: Application to Prostate MRI Segmentation. - Robert Toth; Anant Madabhushi (IEEE Trans. Medical Imaging, 2012)

Anisotropic smoothing regularization (AnSR) in Thirion's Demons registration evaluates brain MRI tissue changes post-laser ablation. - Eileen Hwuang; Shabbar Danish; Mirabela Rusu; Rachel Sparks; Robert Toth; Anant Madabhushi (EMBC, 2013)

Co-occurring gland tensors in localized cluster graphs: Quantitative histomorphometry for predicting biochemical recurrence for intermediate grade prostate cancer. - George Lee 002; Rachel Sparks; Sahirzeeshan Ali; Anant Madabhushi; Michael D. Feldman; Stephen R. Master; Natalie Shih; John Tomaszewski 001 (ISBI, 2013)

Learning based fiducial driven registration (LEFIR): Evaluating laser ablation changes for neurological applications. - Tao Wan 001; B. Nicolas Bloch; Shabbar Danish; Anant Madabhushi (ISBI, 2013)

Discriminatively weighted multi-scale Local Binary Patterns: Applications in prostate cancer diagnosis on T2W MRI. - Haibo Wang; Satish Viswanath; Anant Madabhushi (ISBI, 2013)

Iterative multiple reference tissue method for estimating pharmacokinetic parameters on prostate DCE MRI. - Shoshana B. Ginsburg; B. Nicolas Bloch; Neil M. Rofsky; Elizabeth M. Genega; Robert E. Lenkinski; Anant Madabhushi (Computer-Aided Diagnosis, 2013)

Spatially Aware Cell Cluster(SpACCl) Graphs: Predicting Outcome in Oropharyngeal p16+ Tumors. - Sahirzeeshan Ali; James Lewis; Anant Madabhushi (MICCAI (1), 2013)

A Deep Learning Architecture for Image Representation, Visual Interpretability and Automated Basal-Cell Carcinoma Cancer Detection. - Angel Alfonso Cruz-Roa; John Edison Arevalo Ovalle; Anant Madabhushi; Fabio Augusto González Osorio (MICCAI (2), 2013)

Variable Importance in Nonlinear Kernels (VINK): Classification of Digitized Histopathology. - Shoshana Ginsburg; Sahirzeeshan Ali; George Lee 002; Ajay Basavanhally; Anant Madabhushi (MICCAI (2), 2013)

Cell Orientation Entropy (COrE): Predicting Biochemical Recurrence from Prostate Cancer Tissue Microarrays. - George Lee 002; Sahirzeeshan Ali; Robert Veltri; Jonathan I. Epstein; Christhunesa Christudass; Anant Madabhushi (MICCAI (3), 2013)

Cell cluster graph for prediction of biochemical recurrence in prostate cancer patients from tissue microarrays. - Sahirzeeshan Ali; Robert Veltri; Jonathan A. Epstein; Christhunesa Christudass; Anant Madabhushi (Digital Pathology, 2013)

EM-based segmentation-driven color standardization of digitized histopathology. - Ajay Basavanhally; Anant Madabhushi (Digital Pathology, 2013)

A statistical deformation model (SDM) based regularizer for non-rigid image registration: application to registration of multimodal prostate MRI and histology. - Srivathsan Babu Prabu; Robert Toth; Anant Madabhushi (Digital Pathology, 2013)

Identifying in vivo DCE MRI parameters correlated with ex vivo quantitative microvessel architecture: A radiohistomorphometric approach. - Asha Singanamalli; Rachel Sparks; Mirabela Rusu; Natalie Shih; Amy Ziober; John Tomaszewski 001; Mark Rosen; Michael D. Feldman; Anant Madabhushi (Digital Pathology, 2013)

Fully automated prostate magnetic resonance imaging and transrectal ultrasound fusion via a probabilistic registration metric. - Rachel Sparks; B. Nicolas Bloch; Ernest J. Feleppa; Dean C. Barratt; Anant Madabhushi (Image-Guided Procedures, 2013)

Quantitative evaluation of multi-parametric MR imaging marker changes post-laser interstitial ablation therapy (LITT) for epilepsy. - Pallavi Tiwari; Shabbar Danish; Stephen Wong; Anant Madabhushi (Image-Guided Procedures, 2013)

Quantitative evaluation of treatment related changes on multi-parametric MRI after laser interstitial thermal therapy of prostate cancer. - Satish Viswanath; Robert Toth; Mirabela Rusu; Dan Sperling; Herbert Lepor; Jurgen J. Fütterer; Anant Madabhushi (Image-Guided Procedures, 2013)

Statistical 3D prostate imaging atlas construction via anatomically constrained registration. - Mirabela Rusu; B. Nicolas Bloch; C. Carl Jaffe; Neil Rofsky; Elizabeth Genega; Ernest J. Feleppa; Robert E. Lenkinski; Anant Madabhushi (Image Processing, 2013)

A novel point-based nonrigid image registration scheme based on learning optimal landmark configurations. - Tao Wan 001; B. Nicolas Bloch; Shabbar Danish; Anant Madabhushi (Image Processing, 2013)

Mouse lung volume reconstruction from efficient groupwise registration of individual histological slices with natural gradient. - Haibo Wang; Mirabela Rusu; Thea Golden; Andrew J. Gow; Anant Madabhushi (Image Processing, 2013)

Decision support system for detection of diabetic retinopathy using smartphones. - Prateek Prasanna; Shubham Jain; Neelakshi Bhagat; Anant Madabhushi (PervasiveHealth, 2013)

Statistical shape model for manifold regularization: Gleason grading of prostate histology. - Rachel Sparks; Anant Madabhushi (Comput. Vis. Image Underst., 2013)

Simultaneous segmentation of prostatic zones using Active Appearance Models with multiple coupled levelsets. - Robert Toth; Justin Ribault; John Gentile; Dan Sperling; Anant Madabhushi (Comput. Vis. Image Underst., 2013)

Explicit shape descriptors: Novel morphologic features for histopathology classification. - Rachel Sparks; Anant Madabhushi (Medical Image Anal., 2013)

Multi-kernel graph embedding for detection, Gleason grading of prostate cancer via MRI/MRS. - Pallavi Tiwari; John Kurhanewicz; Anant Madabhushi (Medical Image Anal., 2013)

Multi-Field-of-View Framework for Distinguishing Tumor Grade in ER+ Breast Cancer From Entire Histopathology Slides. - Ajay Basavanhally; Shridar Ganesan; Michael D. Feldman; Natalie Shih; Carolyn Mies; John Tomaszewski 001; Anant Madabhushi (IEEE Trans. Biomed. Eng., 2013)

Computer extracted texture features on T2w MRI to predict biochemical recurrence following radiation therapy for prostate cancer. - Shoshana B. Ginsburg; Mirabela Rusu; John Kurhanewicz; Anant Madabhushi (Computer-Aided Diagnosis, 2014)

Distinguishing prostate cancer from benign confounders via a cascaded classifier on multi-parametric MRI. - Geert J. S. Litjens; R. Elliott; Natalie Shih; Michael D. Feldman; Jelle O. Barentsz; Christina A. Hulsbergen van de Kaa; Iringo Kovacs; Henkjan J. Huisman; Anant Madabhushi (Computer-Aided Diagnosis, 2014)

A prostate MRI atlas of biochemical failures following cancer treatment. - Mirabela Rusu; John Kurhanewicz; Ashutosh Tewari; Anant Madabhushi (Computer-Aided Diagnosis, 2014)

Texture descriptors to distinguish radiation necrosis from recurrent brain tumors on multi-parametric MRI. - Pallavi Tiwari; Prateek Prasanna; Lisa Rogers; Leo Wolansky; Chaitra Badve; Andrew Sloan; Mark Cohen; Anant Madabhushi (Computer-Aided Diagnosis, 2014)

Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing Tumor Confounders and Molecular Subtypes on MRI. - Prateek Prasanna; Pallavi Tiwari; Anant Madabhushi (MICCAI (3), 2014)

Selecting Features with Group-Sparse Nonnegative Supervised Canonical Correlation Analysis: Multimodal Prostate Cancer Prognosis. - Haibo Wang; Asha Singanamalli; Shoshana Ginsburg; Anant Madabhushi (MICCAI (3), 2014)

Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks. - Angel Cruz-Roa; Ajay Basavanhally; Fabio A. González 001; Hannah Gilmore; Michael D. Feldman; Shridar Ganesan; Natalie Shih; John Tomaszewski 001; Anant Madabhushi (Digital Pathology, 2014)

Cascaded ensemble of convolutional neural networks and handcrafted features for mitosis detection. - Haibo Wang; Angel Cruz-Roa; Ajay Basavanhally; Hannah Gilmore; Natalie Shih; Mike Feldman; John Tomaszewski 001; Fabio A. González 001; Anant Madabhushi (Digital Pathology, 2014)

Distinguishing benign confounding treatment changes from residual prostate cancer on MRI following laser ablation. - Geert Litjens 001; Henkjan J. Huisman; R. Elliott; Natalie Shih; Michael D. Feldman; Satish Viswanath; Jurgen J. Fütterer; J. Bomers; Anant Madabhushi (Image-Guided Procedures, 2014)

Identifying MRI markers to evaluate early treatment-related changes post-laser ablation for cancer pain management. - Pallavi Tiwari; Shabbar Danish; Anant Madabhushi (Image-Guided Procedures, 2014)

Spectral embedding-based registration (SERg) for multimodal fusion of prostate histology and MRI. - Eileen Hwuang; Mirabela Rusu; Sudha Karthigeyan; Shannon Agner; Rachel Sparks; Natalie Shih; John Tomaszewski 001; Mark Rosen; Michael D. Feldman; Anant Madabhushi (Image Processing, 2014)

Spatially aware expectation maximization (SpAEM): application to prostate TRUS segmentation. - Mahdi Orooji; Rachel Sparks; B. Nicolas Bloch; Ernest J. Feleppa; Dean C. Barratt; Anant Madabhushi (Image Processing, 2014)

A domain constrained deformable (DoCD) model for co-registration of pre- and post-radiated prostate MRI. - Robert Toth; Bryan J. Traughber; Rodney J. Ellis; John Kurhanewicz; Anant Madabhushi (Neurocomputing, 2014)

Identifying quantitative in vivo multi-parametric MRI features for treatment related changes after laser interstitial thermal therapy of prostate cancer. - Satish Viswanath; Robert Toth; Mirabela Rusu; Dan Sperling; Herbert Lepor; Jurgen J. Fütterer; Anant Madabhushi (Neurocomputing, 2014)

A learning based fiducial-driven registration scheme for evaluating laser ablation changes in neurological disorders. - Tao Wan 001; B. Nicolas Bloch; Shabbar Danish; Anant Madabhushi (Neurocomputing, 2014)

Evaluation of prostate segmentation algorithms for MRI: The PROMISE12 challenge. - Geert Litjens 001; Robert Toth; Wendy J. M. van de Ven; Caroline Hoeks; Sjoerd Kerkstra; Bram van Ginneken; Graham Vincent; Gwenaël Guillard; Neil Birbeck; Jindang Zhang; Robin Strand; Filip Malmberg; et al. (Medical Image Anal., 2014)

Combining Unsupervised Feature Learning and Riesz Wavelets for Histopathology Image Representation: Application to Identifying Anaplastic Medulloblastoma. - Sebastian Otálora; Angel Cruz-Roa; John Edison Arevalo Ovalle; Manfredo Atzori; Anant Madabhushi; Alexander R. Judkins; Fabio A. González 001; Henning Müller; Adrien Depeursinge (MICCAI (1), 2015)

Sparse Non-negative Matrix Factorization (SNMF) based color unmixing for breast histopathological image analysis. - Jun Xu 005; Lei Xiang; Guanhao Wang; Shridar Ganesan; Michael D. Feldman; Natalie N. C. Shih; Hannah Gilmore; Anant Madabhushi (Comput. Medical Imaging Graph., 2015)

Selective invocation of shape priors for deformable segmentation and morphologic classification of prostate cancer tissue microarrays. - Sahirzeeshan Ali; Robert Veltri; Jonathan I. Epstein; Christhunesa Christudass; Anant Madabhushi (Comput. Medical Imaging Graph., 2015)

Assessment of algorithms for mitosis detection in breast cancer histopathology images. - Mitko Veta; Paul J. van Diest; Stefan M. Willems; Haibo Wang; Anant Madabhushi; Angel Cruz-Roa; Fabio A. González 001; Anders Boesen Lindbo Larsen; Jacob S. Vestergaard; Anders B. Dahl; Dan C. Ciresan; Jürgen Schmidhuber; et al. (Medical Image Anal., 2015)

Supervised Multi-View Canonical Correlation Analysis (sMVCCA): Integrating Histologic and Proteomic Features for Predicting Recurrent Prostate Cancer. - George Lee 002; Asha Singanamalli; Haibo Wang; Michael D. Feldman; Stephen R. Master; Natalie N. C. Shih; Elaine Spangler; Timothy R. Rebbeck; John Tomaszewski 001; Anant Madabhushi (IEEE Trans. Medical Imaging, 2015)

Evaluating stability of histomorphometric features across scanner and staining variations: predicting biochemical recurrence from prostate cancer whole slide images. - Patrick Leo; George Lee 002; Anant Madabhushi (Digital Pathology, 2016)

Automated tubule nuclei quantification and correlation with oncotype DX risk categories in ER+ breast cancer whole slide images. - David Romo-Bucheli; Andrew Janowczyk; Eduardo Romero 001; Hannah Gilmore; Anant Madabhushi (Digital Pathology, 2016)

Multi-modality registration via multi-scale textural and spectral embedding representations. - Lin Li; Mirabela Rusu; Satish Viswanath; Gregory Penzias; Shivani Pahwa; Jay Gollamudi; Anant Madabhushi (Image Processing, 2016)

A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images. - Jun Xu 005; Xiaofei Luo; Guanhao Wang; Hannah Gilmore; Anant Madabhushi (Neurocomputing, 2016)

Image analysis and machine learning in digital pathology: Challenges and opportunities. - Anant Madabhushi; George Lee 002 (Medical Image Anal., 2016)

Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images. - Jun Xu 005; Lei Xiang; Qingshan Liu 001; Hannah Gilmore; Jianzhong Wu; Jinghai Tang; Anant Madabhushi (IEEE Trans. Medical Imaging, 2016)

Feature Importance in Nonlinear Embeddings (FINE): Applications in Digital Pathology. - Shoshana B. Ginsburg; George Lee 002; Sahirzeeshan Ali; Anant Madabhushi (IEEE Trans. Medical Imaging, 2016)

Deep Learning Tissue Segmentation in Cardiac Histopathology Images. - Jeffrey J. Nirschl; Andrew Janowczyk; Eliot G. Peyster; Renee Frank; Kenneth B. Margulies; Michael D. Feldman; Anant Madabhushi (Deep Learning for Medical Image Analysis, 2017)

Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma. - Niha G. Beig; Jay Patel; Prateek Prasanna; Sasan Partovi; Vinay Varadan; Anant Madabhushi; Pallavi Tiwari (Computer-Aided Diagnosis, 2017)

Intra-perinodular Textural Transition (Ipris): A 3D Descriptor for Nodule Diagnosis on Lung CT. - Mehdi Alilou; Mahdi Orooji; Anant Madabhushi (MICCAI (3), 2017)

RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing Intra-tumoral Heterogeneity for Response and Outcome Prediction. - Jacob Antunes; Prateek Prasanna; Anant Madabhushi; Pallavi Tiwari; Satish Viswanath (MICCAI (2), 2017)

Field Effect Induced Organ Distension (FOrge) Features Predicting Biochemical Recurrence from Pre-treatment Prostate MRI. - Soumya Ghose; Rakesh Shiradkar; Mirabela Rusu; Jhimli Mitra; Rajat Thawani; Michael D. Feldman; Amar Gupta; Andrei S. Purysko; Lee Ponsky; Anant Madabhushi (MICCAI (2), 2017)

Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An Integrated Descriptor for Brain Tumor Prognosis. - Prateek Prasanna; Jhimli Mitra; Niha G. Beig; Sasan Partovi; Gagandeep Singh; Marco Pinho; Anant Madabhushi; Pallavi Tiwari (MICCAI (2), 2017)

A lymphocyte spatial distribution graph-based method for automated classification of recurrence risk on lung cancer images. - Juan D. García-Arteaga; Germán Corredor; Xiangxue Wang; Vamsidhar Velcheti; Anant Madabhushi; Eduardo Romero 001 (SIPAIM, 2017)

Quantifying expert diagnosis variability when grading tumor-infiltrating lymphocytes. - Paula Toro; Germán Corredor; Xiangxue Wang; Viviana Arias; Vamsidhar Velcheti; Anant Madabhushi; Eduardo Romero 001 (SIPAIM, 2017)

Dimensionality reduction-based fusion approaches for imaging and non-imaging biomedical data: concepts, workflow, and use-cases. - Satish Viswanath; Pallavi Tiwari; George Lee 002; Anant Madabhushi (BMC Medical Imaging, 2017)

Stain Normalization using Sparse AutoEncoders (StaNoSA): Application to digital pathology. - Andrew Janowczyk; Ajay Basavanhally; Anant Madabhushi (Comput. Medical Imaging Graph., 2017)

Empirical evaluation of cross-site reproducibility in radiomic features for characterizing prostate MRI. - Prathyush Chirra; Patrick Leo; Michael Yim; B. Nicolas Bloch; Ardeshir R. Rastinehad; Andrei S. Purysko; Mark Rosen; Anant Madabhushi; Satish Viswanath (Computer-Aided Diagnosis, 2018)

A deep learning classifier for prediction of pathological complete response to neoadjuvant chemotherapy from baseline breast DCE-MRI. - Kavya Ravichandran; Nathaniel Braman; Andrew Janowczyk; Anant Madabhushi (Computer-Aided Diagnosis, 2018)

Vascular Network Organization via Hough Transform (VaNgOGH): A Novel Radiomic Biomarker for Diagnosis and Treatment Response. - Nathaniel Braman; Prateek Prasanna; Mehdi Alilou; Niha G. Beig; Anant Madabhushi (MICCAI (2), 2018)

Feature Driven Local Cell Graph (FeDeG): Predicting Overall Survival in Early Stage Lung Cancer. - Cheng Lu 001; Xiangxue Wang; Prateek Prasanna; Germán Corredor; Geoffrey Sedor; Kaustav Bera; Vamsidhar Velcheti; Anant Madabhushi (MICCAI (2), 2018)

A watershed and feature-based approach for automated detection of lymphocytes on lung cancer images. - Germán Corredor; Xiangxue Wang; Cheng Lu 001; Vamsidhar Velcheti; Eduardo Romero 001; Anant Madabhushi (Digital Pathology, 2018)

Combination of nuclear NF-κB/p65 localization and gland morphological features from surgical specimens appears to be predictive of early biochemical recurrence in prostate cancer patients. - Patrick Leo; Eswar Shankar; Robin Elliott; Andrew Janowczyk; Anant Madabhushi; Sanjay Gupta (Digital Pathology, 2018)

RaPtomics: integrating radiomic and pathomic features for predicting recurrence in early stage lung cancer. - Pranjal Vaidya; Xiangxue Wang; Kaustav Bera; Arjun Khunger; Humberto Choi; Pradnya Patil; Vamsidhar Velcheti; Anant Madabhushi (Digital Pathology, 2018)

A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images. - Andrew Janowczyk; Scott Doyle; Hannah Gilmore; Anant Madabhushi (Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2018)

Multi-tissue Partitioning for Whole Slide Images of Colorectal Cancer Histopathology Images with Deeptissue Net. - Jun Xu 005; Chengfei Cai; Yangshu Zhou; Bo Yao; Geyang Xu; Xiangxue Wang; Ke Zhao; Anant Madabhushi; Zaiyi Liu; Li Liang (ECDP, 2019)

Histopathological Image Analysis on Mouse Testes for Automated Staging of Mouse Seminiferous Tubule. - Jun Xu 005; Haoda Lu; Haixin Li; Xiangxue Wang; Anant Madabhushi; Yujun Xu (ECDP, 2019)

Morphology of vascular network in eyes with diabetic macular edema varies based on tolerance of aflibercept treatment interval length: preliminary findings. - Prateek Prasanna; Justis Ehlers; Nathaniel Braman; Natalia Figueredo; Vishal Bobba; Sumit Sharma 005; Sunil Srivastava; Anant Madabhushi (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2019)

Spatial arrangement of leakage patterns in diabetic macular edema is associated with tolerance of aflibercept treatment interval length: preliminary findings. - Prateek Prasanna; Justis Ehlers; Vishal Bobba; Natalia Figueredo; Cheng Lu 001; Sumit Sharma 005; Sunil Srivastava; Anant Madabhushi (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2019)

Quantitative vessel tortuosity radiomics on baseline non-contrast lung CT predict response to immunotherapy and are prognostic of overall survival. - Mehdi Alilou; Pranjal Vaidya; Mohammadhadi Khorrami; Alexia Zagouras; Pradnya Patil; Kaustav Bera; Pingfu Fu; Vamsidhar Velcheti; Anant Madabhushi (Computer-Aided Diagnosis, 2019)

Radiogenomic characterization of response to chemo-radiation therapy in glioblastoma is associated with PI3K/AKT/mTOR and apoptosis signaling pathways. - Niha G. Beig; Prateek Prasanna; Virginia B. Hill; Ruchika Verma; Vinay Varadan; Anant Madabhushi; Pallavi Tiwari (Computer-Aided Diagnosis, 2019)

Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI. - Sukanya Iyer; Marwa Ismail; Benita Tamrazi; Ashley Margol; Ruchika Verma; Ramon Correa; Prateek Prasanna; Niha G. Beig; Kaustav Bera; Volodymyr Statsevych; Alexander R. Judkins; Anant Madabhushi; et al. (Computer-Aided Diagnosis, 2019)

A combination of intra- and peritumoral features on baseline CT scans is associated with overall survival in non-small cell lung cancer patients treated with immune checkpoint inhibitors: a multi-agent multi-site study. - Mohammadhadi Khorrami; Mehdi Alilou; Prateek Prasanna; Pradnya Patil; Pirya Velu; Kaustav Bera; Pingfu Fu; Vamsidhar Velcheti; Anant Madabhushi (Computer-Aided Diagnosis, 2019)

Radiomic features derived from pre-operative multi-parametric MRI of prostate cancer are associated with Decipher risk score. - Lin Li; Rakesh Shiradkar; Ahmad Algohary; Patrick Leo; Cristina Magi-Galluzzi; Eric Klein; Andrei S. Purysko; Anant Madabhushi (Computer-Aided Diagnosis, 2019)

Radiomics of the lesion habitat on pre-treatment MRI predicts response to chemo-radiation therapy in Glioblastoma. - Ruchika Verma; Ramon Correa; Virginia B. Hill; Niha G. Beig; Abdelkader Mahammedi; Anant Madabhushi; Pallavi Tiwari (Computer-Aided Diagnosis, 2019)

STructural Rectal Atlas Deformation (StRAD) Features for Characterizing Intra- and Peri-wall Chemoradiation Response on MRI. - Jacob Antunes; Zhouping Wei; Charlems Álvarez Jimenez; Eduardo Romero 001; Marwa Ismail; Anant Madabhushi; Pallavi Tiwari; Satish E. Viswanath (MICCAI (4), 2019)

Response Estimation Through Spatially Oriented Neural Network and Texture Ensemble (RESONATE). - Jeffrey E. Eben; Nathaniel Braman; Anant Madabhushi (MICCAI (4), 2019)

Phenotyping tumor infiltrating lymphocytes (PhenoTIL) on H&E tissue images: predicting recurrence in lung cancer. - Cristian Barrera; Germán Corredor; Xiangxue Wang; Kurt A. Schalper; David L. Rimm; Vamsidhar Velcheti; Anant Madabhushi; Eduardo Romero Castro (Digital Pathology, 2019)

Integrating radiomic features from T2-weighted and contrast-enhanced MRI to evaluate pathologic rectal tumor regression after chemoradiation. - Siddhartha Nanda; Jacob T. Antunes; Amrish Selvam; Kaustav Bera; Justin T. Brady; Jayakrishna Gollamudi; Kenneth Friedman; Joseph E. Willis; Conor P. Delaney; Raj M. Paspulati; Anant Madabhushi; Satish E. Viswanath (Image-Guided Procedures, 2019)

Radiomic characterization of perirectal fat on MRI enables accurate assessment of tumor regression and lymph node metastasis in rectal cancers after chemoradiation. - Michael C. Yim; Zhouping Wei; Jacob Antunes; Neil K. R. Sehgal; Kaustav Bera; Justin T. Brady; Kenneth Friedman; Joseph E. Willis; Andrei S. Purysko; Raj M. Paspulati; Anant Madabhushi; Satish E. Viswanath (Image-Guided Procedures, 2019)

Comparing radiomic classifiers and classifier ensembles for detection of peripheral zone prostate tumors on T2-weighted MRI: a multi-site study. - Satish Viswanath; Prathyush Chirra; Michael Yim; Neil M. Rofsky; Andrei S. Purysko; Mark A. Rosen; B. Nicolas Bloch; Anant Madabhushi (BMC Medical Imaging, 2019)

A combination of intra- and peri-tumoral deep features from prostate bi-parametric MRI can distinguish clinically significant and insignificant prostate cancer. - Amogh Hiremath; Rakesh Shiradkar; Nathaniel Braman; Prateek Prasanna; Ardeshir R. Rastinehad; Andrei S. Purysko; Anant Madabhushi (Computer-Aided Diagnosis, 2020)

Multi-site evaluation of stable radiomic features for more accurate evaluation of pathologic downstaging on MRI after chemoradiation for rectal cancers. - Amrish Selvam; Jacob Antunes; Kaustav Bera; Asya Ofshteyn; Justin T. Brady; Katherine Bingmer; Kenneth Friedman; Sharon L. Stein; Rajmohan Paspulati; Andrei S. Purysko; Matthew Kalady; Anant Madabhushi; et al. (Computer-Aided Diagnosis, 2020)

Radiomic features derived from periprostatic fat on pre-surgical T2w MRI predict extraprostatic extension of prostate cancer identified on post-surgical pathology: preliminary results. - Rakesh Shiradkar; Ruyuan Zuo; Amr Mahran; Lee Ponsky; Sree Harsha Tirumani; Anant Madabhushi (Computer-Aided Diagnosis, 2020)

Computationally derived cytological image markers for predicting risk of relapse in acute myeloid leukemia patients following bone marrow transplantation. - Sara ArabYarmohammadi; Zelin Zhang; Patrick Leo; Marjan Firouznia; Andrew Janowczyk; Haojia Li; Nathaniel M. Braman; Kaustav Bera; Behtash G. Nezami; Howard Meyerson; Jun Xu 005; Leland Metheny; et al. (Digital Pathology, 2020)

Computer extracted features related to the spatial arrangement of tumor-infiltrating lymphocytes predict overall survival in epithelial ovarian cancer receiving adjuvant chemotherapy. - Sepideh Azarianpour; Germán Corredor; Kaustav Bera; Patrick Leo; Nathaniel Braman; Pingfu Fu; Haider Mahdi; Anant Madabhushi (Digital Pathology, 2020)

Compactness measures of tumor infiltrating lymphocytes in lung adenocarcinoma are associated with overall patient survival and immune scores. - Ruiwen Ding; Prateek Prasanna; Germán Corredor; Cheng Lu 001; Priya Velu; Khoi Le; Patrick Leo; Niha G. Beig; Vamsidhar Velcheti; David L. Rimm; Kurt A. Schalper; Anant Madabhushi (Digital Pathology, 2020)

Three-dimensional histo-morphometric features from light sheet microscopy images result in improved discrimination of benign from malignant glands in prostate cancer. - Can Fahrettin Koyuncu; Andrew Janowczyk; Cheng Lu 001; Patrick Leo; Mehdi Alilou; Adam K. Glaser; Nicholas P. Reder; Jonathan T. C. Liu; Anant Madabhushi (Digital Pathology, 2020)

Texture features distinguish benign cell clusters from adenocarcinomas on bile duct brushing cytology images. - Shayan Monabbati; Patrick Leo; Kaustav Bera; Behtash G. Nezami; Claire W. Michael; Aparna Harbhajanka; Anant Madabhushi (Digital Pathology, 2020)

Automated gleason grading on prostate biopsy slides by statistical representations of homology profile. - Chaoyang Yan; Kazuaki Nakane; Xiangxue Wang; Yao Fu; Haoda Lu; Xiangshan Fan; Michael D. Feldman; Anant Madabhushi; Jun Xu 005 (Comput. Methods Programs Biomed., 2020)

Deep learning-based prediction of response to HER2-targeted neoadjuvant chemotherapy from pre-treatment dynamic breast MRI: A multi-institutional validation study. - Nathaniel Braman; Mohammed El Adoui; Manasa Vulchi; Paulette Turk; Maryam Etesami; Pingfu Fu; Kaustav Bera; Stylianos Drisis; Vinay Varadan; Donna Plecha; Mohammed Benjelloun; Jame Abraham; et al. (CoRR, 2020)

MRQy: An Open-Source Tool for Quality Control of MR Imaging Data. - Amir Reza Sadri; Andrew Janowczyk; Ren Zou; Ruchika Verma; Jacob Antunes; Anant Madabhushi; Pallavi Tiwari; Satish E. Viswanath (CoRR, 2020)

Can tumor location on pre-treatment MRI predict likelihood of pseudo-progression versus tumor recurrence in Glioblastoma? A feasibility study. - Marwa Ismail; Virginia B. Hill; Volodymyr Statsevych; Evan Mason; Ramon Correa; Prateek Prasanna; Gagandeep Singh; Kaustav Bera; Rajat Thawani; Anant Madabhushi; Manmeet Ahluwalia; Pallavi Tiwari (CoRR, 2020)

A review of deep learning in medical imaging: Image traits, technology trends, case studies with progress highlights, and future promises. - S. Kevin Zhou; Hayit Greenspan; Christos Davatzikos; James S. Duncan; Bram van Ginneken; Anant Madabhushi; Jerry L. Prince; Daniel Rueckert; Ronald M. Summers (CoRR, 2020)

Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma? - A Feasibility Study. - Marwa Ismail; Virginia B. Hill; Volodymyr Statsevych; Evan Mason; Ramon Correa; Prateek Prasanna; Gagandeep Singh; Kaustav Bera; Rajat Thawani; Manmeet Ahluwalia; Anant Madabhushi; Pallavi Tiwari (Frontiers Comput. Neurosci., 2020)

LuMiRa: An Integrated Lung Deformation Atlas and 3D-CNN Model of Infiltrates for COVID-19 Prognosis. - Amogh Hiremath; Lei Yuan; Rakesh Shiradkar; Kaustav Bera; Vidya Sankar Viswanathan; Pranjal Vaidya; Jennifer Furin; Keith Armitage; Robert Gilkeson; Mengyao Ji; Pingfu Fu; Amit Gupta; et al. (MICCAI (7), 2021)

SPARTA: An Integrated Stability, Discriminability, and Sparsity Based Radiomic Feature Selection Approach. - Amir Reza Sadri; Sepideh Azarianpour Esfahani; Prathyush Chirra; Jacob Antunes; Pavithran Pattiam Giriprakash; Patrick Leo; Anant Madabhushi; Satish E. Viswanath (MICCAI (3), 2021)

A new machine learning approach for predicting likelihood of recurrence following ablation for atrial fibrillation from CT. - Thomas Atta-Fosu; Michael LaBarbera; Soumya Ghose; Paul Schoenhagen; Walid Saliba; Patrick J. Tchou; Bruce D. Lindsay; Milind Y. Desai; Deborah Kwon; Mina K. Chung; Anant Madabhushi (BMC Medical Imaging, 2021)

Computerized spermatogenesis staging (CSS) of mouse testis sections via quantitative histomorphological analysis. - Jun Xu 005; Haoda Lu; Haixin Li; Chaoyang Yan; Xiangxue Wang; Min Zang; Dirk G. de Rooij; Anant Madabhushi; Eugene Yujun Xu (Medical Image Anal., 2021)

Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers. - Cheng Lu 001; Can Koyuncu 001; Germán Corredor; Prateek Prasanna; Patrick Leo; Xiangxue Wang; Andrew Janowczyk; Kaustav Bera; James S. Lewis Jr.; Vamsidhar Velcheti; Anant Madabhushi (Medical Image Anal., 2021)

Special issue on computational pathology: An overview. - Anant Madabhushi; Constantino Carlos Reyes-Aldasoro (Medical Image Anal., 2021)

A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises. - S. Kevin Zhou; Hayit Greenspan; Christos Davatzikos; James S. Duncan; Bram van Ginneken; Anant Madabhushi; Jerry L. Prince; Daniel Rueckert; Ronald M. Summers (Proc. IEEE, 2021)

Imaging Features of Vessels and Leakage Patterns Predict Extended Interval Aflibercept Dosing Using Ultra-Widefield Angiography in Retinal Vascular Disease: Findings From the PERMEATE Study. - Azam Moosavi; Natalia Figueiredo; Prateek Prasanna; Sunil K. Srivastava; Sumit Sharma 005; Anant Madabhushi; Justis P. Ehlers (IEEE Trans. Biomed. Eng., 2021)

Integrated Clinical and CT Based Artificial Intelligence Nomogram for Predicting Severity and Need for Ventilator Support in COVID-19 Patients: A Multi-Site Study. - Amogh Hiremath; Kaustav Bera; Lei Yuan; Pranjal Vaidya; Mehdi Alilou; Jennifer Furin; Keith Armitage; Robert Gilkeson; Mengyao Ji; Pingfu Fu; Amit Gupta; Cheng Lu 001; et al. (IEEE J. Biomed. Health Informatics, 2021)

Evaluating the sensitivity of deep learning to inter-reader variations in lesion delineations on bi-parametric MRI in identifying clinically significant prostate cancer. - Ansh Roge; Amogh Hiremath; Michael Sobota; Sree Harsha Tirumani; Leonardo Kayat Bittencourt; Justin Ream; Ryan Ward; Halimat Olaniyan; Sadhna Verma; Andrei S. Purysko; Anant Madabhushi; Rakesh Shiradkar (Computer-Aided Diagnosis, 2022)

Computer extracted features of tumor-infiltrating lymphocytes (TILs) architecture are prognostic of progression-free survival in stage III colon cancer. - Aya Aqeel; Germán Corredor; Vidya Sankar Viswanathan; Chuheng Chen; Mogjan Mokhtari; Pingfu Fu; Joseph E. Willis; Anant Madabhushi (Digital and Computational Pathology, 2022)

Identifying the origination of liver metastasis using a hand-crafted computational pathology approach. - Chuheng Chen; Cheng Lu 001; Joseph E. Willis; Anant Madabhushi (Digital and Computational Pathology, 2022)

Quantitative histomorphometric features of tumor nuclei are prognostic of disease-free survival in papillary thyroid carcinoma. - Shayan Monabbati; Paula Toro; Kaustav Bera; Pingfu Fu; Sylvia A. Lou; Anant Madabhushi (Digital and Computational Pathology, 2022)

Survival prediction on intrahepatic cholangiocarcinoma with histomorphological analysis on the whole slide images. - Jiawei Xie; Xiaohong Pu; Jian He; Yudong Qiu; Cheng Lu 001; Wei Gao 003; Xiangxue Wang; Haoda Lu; Jiong Shi; Yuemei Xu; Anant Madabhushi; Xiangshan Fan; et al. (Comput. Biol. Medicine, 2022)

Novel Radiomic Measurements of Tumor- Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers. - Nathaniel Braman; Prateek Prasanna; Kaustav Bera; Mehdi Alilou; Mohammadhadi Khorrami; Patrick Leo; Maryam Etesami; Manasa Vulchi; Paulette Turk; Amit Gupta; Prantesh Jain; Pingfu Fu; et al. (CoRR, 2022)

RADIomic Spatial TexturAl Descriptor (RADISTAT): Quantifying Spatial Organization of Imaging Heterogeneity Associated With Tumor Response to Treatment. - Jacob T. Antunes; Marwa Ismail; Imran Hossain; Zhoumengdi Wang; Prateek Prasanna; Anant Madabhushi; Pallavi Tiwari; Satish E. Viswanath (IEEE J. Biomed. Health Informatics, 2022)

Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to Characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma. - Marwa Ismail; Prateek Prasanna; Kaustav Bera; Volodymyr Statsevych; Virginia B. Hill; Gagandeep Singh; Sasan Partovi; Niha G. Beig; Sean D. McGarry; Peter S. LaViolette; Manmeet Ahluwalia; Anant Madabhushi; et al. (IEEE Trans. Medical Imaging, 2022)

Triangular Analysis of Geographical Interplay of Lymphocytes (TriAnGIL): Predicting Immunotherapy Response in Lung Cancer. - Sara ArabYarmohammadi; Germán Corredor; Yufei Zhou; Miguel López de Rodas; Kurt A. Schalper; Anant Madabhushi (MICCAI (6), 2023)

STAR-Echo: A Novel Biomarker for Prognosis of MACE in Chronic Kidney Disease Patients Using Spatiotemporal Analysis and Transformer-Based Radiomics Models. - Rohan Dhamdhere; Gourav Modanwal; Mohamed H. E. Makhlouf; Neda Shafiabadi Hassani; Satvika Bharadwaj; Pingfu Fu; Ioannis Milioglou; Mahboob Rahman; Sadeer Al-Kindi; Anant Madabhushi (MICCAI (6), 2023)

Spatial connectivity of tumor and associated cells (SpaCell): a novel computational pathology biomarker. - Germán Corredor; Can Koyuncu 001; Andrew Janowczyk; Paula Toro; Sepideh Azarianpour; James S. Lewis Jr.; Anant Madabhushi (Digital and Computational Pathology, 2023)

Biopsy and surgical specimen specific deep learning models for prostate cancer detection on digitized pathology images. - Brennan T. Flannery; Priti Lal; Michael D. Feldman; María Natalizio; Juan C. Santa-Rosario; Anant Madabhushi (Digital and Computational Pathology, 2023)

A pathomic study for risk stratification and unraveling molecular associations of different histologic subtypes of papillary thyroid cancer. - Shayan Monabbati; Sirvan Khalighi; Pingfu Fu; Sylvia Asa; Anant Madabhushi (Digital and Computational Pathology, 2023)

Transformer as a spatially-aware multi-instance learning framework to predict the risk of death for early-stage non-small cell lung cancer. - Yufei Zhou; Can Koyuncu 001; Cristian Barrera; Germán Corredor; Xiangxue Wang; Cheng Lu 001; Anant Madabhushi (Digital and Computational Pathology, 2023)

Resolving impact of technical and biological variability on the convolutional neural networks: evaluating chest x-ray scans. - Dmitry Cherezov; Vidya Sankar Viswanathan; Amit Gupta; Anant Madabhushi (Image Processing, 2023)

Breast Cancer Immunohistochemical Image Generation: a Benchmark Dataset and Challenge Review. - Chuang Zhu; Shengjie Liu; Feng Xu; Zekuan Yu; Arpit Aggarwal; Germán Corredor; Anant Madabhushi; Qixun Qu; Hongwei Fan; Fangda Li; Yueheng Li; Xianchao Guan; et al. (CoRR, 2023)

CohortFinder: an open-source tool for data-driven partitioning of biomedical image cohorts to yield robust machine learning models. - Fan Fan; Georgia Martinez; Thomas DeSilvio; John Shin; Yijiang Chen; Bangchen Wang; Takaya Ozeki; Maxime W. Lafarge; Viktor H. Koelzer; Laura Barisoni; Anant Madabhushi; Satish E. Viswanath; et al. (CoRR, 2023)

Multi-site cross-organ calibrated deep learning (MuSClD): Automated diagnosis of non-melanoma skin cancer. - Yufei Zhou; Can Koyuncu 001; Cheng Lu 001; Rainer Grobholz; Ian Katz; Anant Madabhushi; Andrew Janowczyk (Medical Image Anal., 2023)

Novel Fractal-Based Sub-RPE Compartment OCT Radiomics Biomarkers Are Associated With Subfoveal Geographic Atrophy in Dry AMD. - Sudeshna Sil Kar; Hasan Cetin; Joseph Abraham; Sunil K. Srivastava; Jon Whitney; Anant Madabhushi; Justis P. Ehlers (IEEE Trans. Biomed. Eng., 2023)

Interpretable Survival Risk Prediction for High-Grade Glioma Patients via Radiomic Features from Peritumoral Region. - Rohan Dhamdhere; Satvika Bharadwaj; Arpit Aggarwal; Pushkar Mutha; Wenqi Shi; Benoit Marteau; Anant Madabhushi; May D. Wang (EMBC, 2024)

Deep learning reveals lung shape differences on baseline chest CT between mild and severe COVID-19: A multi-site retrospective study. - Amogh Hiremath; Vidya Sankar Viswanathan; Kaustav Bera; Rakesh Shiradkar; Lei Yuan; Keith Armitage; Robert Gilkeson; Mengyao Ji; Pingfu Fu; Amit Gupta; Cheng Lu 001; Anant Madabhushi (Comput. Biol. Medicine, 2024)

Rank acquisition impact on radiomics estimation (AсquIRE) in chest CT imaging: A retrospective multi-site, multi-use-case study. - Dmitry Cherezov; Vidya Sankar Viswanathan; Pingfu Fu; Amit Gupta; Anant Madabhushi (Comput. Methods Programs Biomed., 2024)

PatchSorter: a high throughput deep learning digital pathology tool for object labeling. - Cedric Walker; Tasneem Talawalla; Robert Toth; Akhil Ambekar; Kien Rea; Oswin Chamian; Fan Fan; Sabina Berezowska; Sven Rottenberg; Anant Madabhushi; Marie Maillard; Laura Barisoni; et al. (npj Digit. Medicine, 2024)

Automatic myeloblast segmentation in acute myeloid leukemia images based on adversarial feature learning. - Zelin Zhang; Sara ArabYarmohammadi; Patrick Leo; Howard Meyerson; Leland Metheny; Jun Xu 005; Anant Madabhushi (Comput. Methods Programs Biomed., 2024)

Non-Invasive Molecular Classification of Gliomas Using Explainable ai and Radiomic Features from Multi-Sequence MRI. - Satvik R. Elayavalli; Ipsa Yadav; Grant T. Cookson; Elias Sharifi; Tanya Tvrdic; Anant Madabhushi; Brent D. Weinberg; Malak Abedalthagafi; Sirvan Khalighi (ISBI, 2025)

UNETVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM. - Xuhui Guo; Tanmoy Dam; Rohan Dhamdhere; Gourav Modanwal; Anant Madabhushi (ISBI, 2025)

When multiple instance learning meets foundation models: Advancing histological whole slide image analysis. - Hongming Xu 002; Mingkang Wang; Duanbo Shi; Huamin Qin; Yunpeng Zhang; Zaiyi Liu; Anant Madabhushi; Peng Gao; Fengyu Cong; Cheng Lu 001 (Medical Image Anal., 2025)