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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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

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)

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)

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)

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)

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)

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)

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)

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)

Opportunities and Advances in Radiomics and Radiogenomics in Neuro-Oncology. - Kaustav Bera; Niha G. Beig; Pallavi Tiwari (RNO-AI@MICCAI, 2019)

"Lesion-habitat" radiomics to distinguish radiation necrosis from tumor recurrence on post-treatment MRI in metastatic brain tumors. - Ramon Correa; Qiu Lei; Jonathan Chen; Johnathan Zeng; Jennifer Yu; Pallavi Tiwari (Computer-Aided Diagnosis, 2020)

Combining deep and hand-crafted MRI features for identifying sex-specific differences in autism spectrum disorder versus controls. - Yashas Hiremath; Marwa Ismail; Ruchika Verma; Jacob Antunes; Pallavi Tiwari (Computer-Aided Diagnosis, 2020)

Spatial-And-Context Aware (SpACe) "Virtual Biopsy" Radiogenomic Maps to Target Tumor Mutational Status on Structural MRI. - Marwa Ismail; Ramon Correa; Kaustav Bera; Ruchika Verma; Anas Saeed Bamashmos; Niha G. Beig; Jacob Antunes; Prateek Prasanna; Volodymyr Statsevych; Manmeet Ahluwalia; Pallavi Tiwari (MICCAI (2), 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)

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)

Multiclass Classification of Disease Using CNN and SVM of Medical Imaging. - Pallavi Tiwari; Deepak Upadhyay; Bhaskar Pant; Noor Mohd (ICACDS (2), 2022)

A radiomics approach to distinguish non-contrast enhancing tumor from vasogenic edema on multi-parametric pre-treatment MRI scans for glioblastoma tumors. - Ipsa Yadav; Marwa Ismail; Volodymyr Statsevych; Virginia B. Hill; Ramon Correa; Manmeet Ahluwalia; Pallavi Tiwari (Computer-Aided Diagnosis, 2022)

A hierarchical deep learning approach for segmentation of glioblastoma tumor niches on digital histopathology. - Alvaro Sandino Garzon; Ruchika Verma; Yijang Chen; David Becerra Tovar; Eduardo Romero Castro; Pallavi Tiwari (Digital and Computational Pathology, 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)

Self-supervised deep learning to predict molecular markers from routine histopathology slides for high-grade glioma tumors. - Olivia Krebs; Shobhit Agarwal; Pallavi Tiwari (Digital and Computational Pathology, 2023)

Graph-Radiomics Learning (GrRAiL): Application to Distinguishing Glioblastoma Recurrence from Pseudo-Progression on Structural MRI. - Dheerendranath Battalapalli; Apoorva Safai; Marwa Ismail; Virginia B. Hill; Volodymyr Statsevych; Raymond Huang; Manmeet Ahluwalia; Pallavi Tiwari (ISBI, 2024)

Multi-Scale Co-Attention Transformer Model to Integrate Radiology, Histology, and Genomics: Application to Survival Prediction in Glioblastoma. - Olivia Krebs; Pallavi Tiwari (ISBI, 2024)

Human-in-the-Loop (HITL) Learning for Identifying Glioblastoma Hallmarks on H&E Slides. - Alvaro A. Sandino; Olivia Krebs; David Becerra; Nelly J. Sandino; Jeffrey Helgager; Eduardo Romero 001; Pallavi Tiwari (ISBI, 2024)

ResNCT: A Deep Learning Model for the Synthesis of Nephrographic Phase Images in CT Urography. - Syed Jamal Safdar Gardezi; Lucas Aronson; Peter Wawrzyn; Hongkun Yu 004; E. Jason Abel; Daniel D. Shapiro; Meghan G. Lubner; Joshua D. Warner; Giuseppe Toia; Lu Mao; Pallavi Tiwari; Andrew L. Wentland (CoRR, 2024)

Adaptive Aggregation Weights for Federated Segmentation of Pancreas MRI. - Hongyi Pan; Gorkem Durak; Zheyuan Zhang; Yavuz Taktak; Elif Keles; Ertugrul Aktas; Alpay Medetalibeyoglu; Yury Velichko; Concetto Spampinato; Ivo Schoots; Marco J. Bruno; Rajesh N. Keswani; et al. (CoRR, 2024)

Adaptive Aggregation Weights for Federated Segmentation of Pancreas MRI. - Hongyi Pan; Gorkem Durak; Zheyuan Zhang; Yavuz Taktak; Elif Keles; Halil Ertugrul Aktas; Alpay Medetalibeyoglu; Yury Velichko; Concetto Spampinato; Ivo Schoots; Marco J. Bruno; Rajesh N. Keswani; et al. (ISBI, 2025)

IPMN Risk Assessment Under Federated Learning Paradigm. - Hongyi Pan; Ziliang Hong; Gorkem Durak; Elif Keles; Halil Ertugrul Aktas; Yavuz Taktak; Alpay Medetalibeyoglu; Zheyuan Zhang; Yury Velichko; Concetto Spampinato; Ivo Schoots; Marco J. Bruno; et al. (ISBI, 2025)

Large-scale multi-center CT and MRI segmentation of pancreas with deep learning. - Zheyuan Zhang; Elif Keles; Gorkem Durak; Yavuz Taktak; Onkar Susladkar; Vandan Gorade; Debesh Jha; Asli C. Ormeci; Alpay Medetalibeyoglu; Lanhong Yao; Bin Wang 068; Ilkin Sevgi Isler; et al. (Medical Image Anal., 2025)

3D Nephrographic Image Synthesis in CT Urography with the Diffusion Model and Swin Transformer. - Hongkun Yu 004; Syed Jamal Safdar Gardezi; E. Jason Abel; Daniel D. Shapiro; Meghan G. Lubner; Joshua D. Warner; Matthew Smith; Giuseppe Toia; Lu Mao; Pallavi Tiwari; Andrew L. Wentland (CoRR, 2025)

Cyst-X: AI-Powered Pancreatic Cancer Risk Prediction from Multicenter MRI in Centralized and Federated Learning. - Hongyi Pan; Gorkem Durak; Elif Keles; Deniz Seyithanoglu; Zheyuan Zhang; Alpay Medetalibeyoglu; Halil Ertugrul Aktas; Andrea Mia Bejar; Ziliang Hong; Yavuz Taktak; Gulbiz Dagoglu Kartal; Sukru Mehmet Erturk; et al. (CoRR, 2025)