Fast, Processor-Cardinality Agnostic PRNG with a Tracking Application. - Andrew Janowczyk; Sharat Chandran; Srinivas Aluru (ICVGIP, 2008)

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)

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)

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)

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)

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

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)

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)

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)

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

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)

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)

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)

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)

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)

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)

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)

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)

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)

HoverFast: an accurate, high-throughput, clinically deployable nuclear segmentation tool for brightfield digital pathology images. - Petros Liakopoulos; Julien Massonnet; Jonatan Bonjour; Medya Tekes Mizrakli; Simon Graham; Michel A. Cuendet; Amanda H. Seipel; Olivier Michielin; Doron Merkler; Andrew Janowczyk (J. Open Source Softw., 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)