Spatial Segmentation of Temporal Texture Using Mixture Linear Models. - Lee Cooper 001; Jun Liu 043; Kun Huang 001 (WDV, 2006)

An imaging workflow for characterizing phenotypical change in large histological mouse model datasets. - Kishore Mosaliganti; Tony Pan; Randall Ridgway; Richard Sharp; Lee Cooper 001; Alex Gulacy; Ashish Sharma 001; M. Okan Irfanoglu; Raghu Machiraju; Tahsin M. Kurç; Alain de Bruin; Pamela Wenzel; et al. (J. Biomed. Informatics, 2008)

Reconstruction of Cellular Biological Structures from Optical Microscopy Data. - Kishore Mosaliganti; Lee Cooper 001; Richard Sharp; Raghu Machiraju; Gustavo Leone; Kun Huang 001; Joel H. Saltz (IEEE Trans. Vis. Comput. Graph., 2008)

Feature-based registration of histopathology images with different stains: An application for computerized follicular lymphoma prognosis. - Lee Cooper 001; Olcay Sertel; Jun Kong 002; Gerard Lozanski; Kun Huang 001; Metin N. Gurcan (Comput. Methods Programs Biomed., 2009)

Non-rigid Registration for Large Sets of Microscopic Images on Graphics Processors. - Antonio Ruiz; Manuel Ujaldon; Lee Cooper 001; Kun Huang 001 (J. Signal Process. Syst., 2009)

Two-point correlation as a feature for histology images: Feature space structure and correlation updating. - Lee Cooper 001; Joel H. Saltz; Raghu Machiraju; Kun Huang 001 (CVPR Workshops, 2010)

High-Performance Systems for in Silico Microscopy Imaging Studies. - Fusheng Wang 001; Tahsin M. Kurç; Patrick M. Widener; Tony Pan; Jun Kong 002; Lee Cooper 001; David A. Gutman; Ashish Sharma 001; Sharath R. Cholleti; Vijay Kumar (DILS, 2010)

Texture based image recognition in microscopy images of diffuse gliomas with multi-class gentle boosting mechanism. - Jun Kong 002; Lee Cooper 001; Ashish Sharma 001; Tahsin M. Kurç; Daniel J. Brat; Joel H. Saltz (ICASSP, 2010)

High Performance Computing Techniques for Scaling Image Analysis Workflows. - Patrick M. Widener; Tahsin M. Kurç; Wenjin Chen; Fusheng Wang 001; Lin Yang 002; Jun Hu; Vijay Kumar; Vicky Chu; Lee Cooper 001; Jun Kong 002; Ashish Sharma 001; Tony Pan; et al. (PARA (2), 2010)

An Integrative Approach for In Silico Glioma Research. - Lee A. D. Cooper; Jun Kong 002; David A. Gutman; Fusheng Wang 001; Sharath R. Cholleti; Tony C. Pan; Patrick M. Widener; Ashish Sharma 001; Tom Mikkelsen; Adam E. Flanders; Daniel L. Rubin; Erwin G. Van Meir; et al. (IEEE Trans. Biomed. Eng., 2010)

Towards building computerized image analysis framework for nucleus discrimination in microscopy images of diffuse glioma. - Jun Kong 002; Lee Cooper 001; Tahsin M. Kurç; Daniel J. Brat; Joel H. Saltz (EMBC, 2011)

In silico analysis of nuclei in glioblastoma using large-scale microscopy images improves prediction of treatment response. - Jun Kong 002; Lee Cooper 001; Carlos Sanchez Moreno; Fusheng Wang 001; Tahsin M. Kurç; Joel H. Saltz; Daniel J. Brat (EMBC, 2011)

Acceleration of Two Point Correlation Function Calculation for Pathology Image Segmentation. - Lee A. D. Cooper; Joel H. Saltz; Ümit V. Çatalyürek; Kun Huang 001 (HISB, 2011)

Parallel Automatic Registration of Large Scale Microscopic Images on Multiprocessor CPUs and GPUs. - Lee Cooper 001; Kun Huang 001; Manuel Ujaldon (IPDPS Workshops, 2011)

Morphological signatures and genomic correlates in glioblastoma. - Lee A. D. Cooper; Jun Kong 002; Fusheng Wang 001; Tahsin M. Kurç; Carlos Sanchez Moreno; Daniel J. Brat; Joel H. Saltz (ISBI, 2011)

A comprehensive framework for classification of nuclei in digital microscopy imaging: An application to diffuse gliomas. - Jun Kong 002; Lee Cooper 001; Fusheng Wang 001; Candace Chisolm; Carlos Sanchez Moreno; Tahsin M. Kurç; Patrick M. Widener; Daniel J. Brat; Joel H. Saltz (ISBI, 2011)

A new steerable pressure force for parametric deformable models. - Jun Kong 002; Lee Cooper 001; Ashish Sharma 001; Tahsin M. Kurç; Daniel J. Brat; Joel H. Saltz (Image Processing, 2011)

Integrative, Multimodal Analysis of Glioblastoma Using TCGA Molecular Data, Pathology Images, and Clinical Outcomes. - Jun Kong 002; Lee A. D. Cooper; Fusheng Wang 001; David A. Gutman; Jingjing Gao; Candace Chisolm; Ashish Sharma 001; Tony Pan; Erwin G. Van Meir; Tahsin M. Kurç; Carlos Sanchez Moreno; Joel H. Saltz; et al. (IEEE Trans. Biomed. Eng., 2011)

High Performance Computing for Integrative Analysis of Large Pathology Image Datasets. - Tahsin M. Kurç; Joel H. Saltz; George Teodoro; Tony Pan; Lee A. D. Cooper; Jun Kong 002; David A. Gutman; Daniel J. Brat; Fusheng Wang 001 (AMIA, 2012)

ZPEG: A hybrid DPCM-DCT based approach for compression of Z-stack images. - Sourabh Khire; Lee Cooper 001; Yuna Park; Alexis B. Carter; Nikil Jayant; Joel H. Saltz (EMBC, 2012)

Accelerating Large Scale Image Analyses on Parallel, CPU-GPU Equipped Systems. - George Teodoro; Tahsin M. Kurç; Tony Pan; Lee A. D. Cooper; Jun Kong 002; Patrick M. Widener; Joel H. Saltz (IPDPS, 2012)

High-throughput Execution of Hierarchical Analysis Pipelines on Hybrid Cluster Platforms - George Teodoro; Tony Pan; Tahsin M. Kurç; Jun Kong 002; Lee A. D. Cooper; Joel H. Saltz (CoRR, 2012)

Integrated morphologic analysis for the identification and characterization of disease subtypes. - Lee A. D. Cooper; Jun Kong 002; David A. Gutman; Fusheng Wang 001; Jingjing Gao; Christina Appin; Sharath R. Cholleti; Tony Pan; Ashish Sharma 001; Lisa Scarpace; Tom Mikkelsen; Tahsin M. Kurç; et al. (J. Am. Medical Informatics Assoc., 2012)

Digital Pathology: Data-Intensive Frontier in Medical Imaging. - Lee A. D. Cooper; Alexis B. Carter; Alton B. Farris; Fusheng Wang 001; Jun Kong 002; David A. Gutman; Patrick M. Widener; Tony C. Pan; Sharath R. Cholleti; Ashish Sharma 001; Tahsin M. Kurç; Daniel J. Brat; et al. (Proc. IEEE, 2012)

High-performance computational analysis of glioblastoma pathology images with database support identifies molecular and survival correlates. - Jun Kong 002; Fusheng Wang 001; George Teodoro; Lee Cooper 001; Carlos Sanchez Moreno; Tahsin M. Kurç; Tony Pan; Joel H. Saltz; Daniel J. Brat (BIBM, 2013)

High-throughput Analysis of Large Microscopy Image Datasets on CPU-GPU Cluster Platforms. - George Teodoro; Tony Pan; Tahsin M. Kurç; Jun Kong 002; Lee A. D. Cooper; Norbert Podhorszki; Scott Klasky; Joel H. Saltz (IPDPS, 2013)

Comparative Performance Analysis of Intel Xeon Phi, GPU, and CPU. - George Teodoro; Tahsin M. Kurç; Jun Kong 002; Lee Cooper 001; Joel H. Saltz (CoRR, 2013)

Feature-based analysis of large-scale spatio-temporal sensor data on hybrid architectures. - Joel H. Saltz; George Teodoro; Tony Pan; Lee A. D. Cooper; Jun Kong 002; Scott Klasky; Tahsin M. Kurç (Int. J. High Perform. Comput. Appl., 2013)

Research and applications: Cancer Digital Slide Archive: an informatics resource to support integrated in silico analysis of TCGA pathology data. - David A. Gutman; Jake Cobb; Dhananjaya Somanna; Yuna Park; Fusheng Wang 001; Tahsin M. Kurç; Joel H. Saltz; Daniel J. Brat; Lee A. D. Cooper (J. Am. Medical Informatics Assoc., 2013)

Efficient irregular wavefront propagation algorithms on hybrid CPU-GPU machines. - George Teodoro; Tony Pan; Tahsin M. Kurç; Jun Kong 002; Lee A. D. Cooper; Joel H. Saltz (Parallel Comput., 2013)

Comparative Performance Analysis of Intel (R) Xeon Phi (TM), GPU, and CPU: A Case Study from Microscopy Image Analysis. - George Teodoro; Tahsin M. Kurç; Jun Kong 002; Lee Cooper 001; Joel H. Saltz (IPDPS, 2014)

Region Templates: Data Representation and Management for Large-Scale Image Analysis. - George Teodoro; Tony Pan; Tahsin M. Kurç; Jun Kong 002; Lee Cooper 001; Scott Klasky; Joel H. Saltz (CoRR, 2014)

Region templates: Data representation and management for high-throughput image analysis. - George Teodoro; Tony Pan; Tahsin M. Kurç; Jun Kong 002; Lee Cooper 001; Scott Klasky; Joel H. Saltz (Parallel Comput., 2014)

Spatiotemporal visualization of cell membrane dynamics and protein colocalization reveals correlation between membrane dynamics and metastatic invasion. - Yue Hou; Lee Cooper 001; Scott Wilkinson; Adam I. Marcus; Daniel J. Brat (BCB, 2015)

An interactive learning framework for scalable classification of pathology images. - Michael Nalisnik; David A. Gutman; Jun Kong 002; Lee A. D. Cooper (IEEE BigData, 2015)

Scalable analysis of Big pathology image data cohorts using efficient methods and high-performance computing strategies. - Tahsin M. Kurç; Xin Qi 007; Daihou Wang; Fusheng Wang 001; George Teodoro; Lee Cooper 001; Michael Nalisnik; Lin Yang 002; Joel H. Saltz; David J. Foran (BMC Bioinform., 2015)

Quantitative Imaging and Imaging Informatics in the Era of Precision Medicine. - Lee Cooper 001; Jayashree Kalpathy-Cramer; William Hsu; Ashish Sharma 001 (AMIA, 2016)

Learning Genomic Representations to Predict Clinical Outcomes in Cancer. - Safoora Yousefi; Congzheng Song; Nelson Nauata; Lee Cooper 001 (CoRR, 2016)

Session Introduction. - Li Shen 001; Lee A. D. Cooper (PSB, 2017)

Vectorized persistent homology representations for characterizing glandular architecture in histology images. - Deepak Roy Chittajallu; Neal Siekierski; Sanghoon Lee 007; Samuel Gerber; Jonathan D. Beezley; David Manthey; David A. Gutman; Lee Cooper 001 (ISBI, 2018)

The OncoPPi Portal: an integrative resource to explore and prioritize protein-protein interactions for cancer target discovery. - Andrei A. Ivanov; Brian Revennaugh; Lauren Rusnak; Valentina Gonzalez-Pecchi; Xiulei Mo; Margaret A. Johns; Yuhong Du; Lee A. D. Cooper; Carlos Sanchez Moreno; Fadlo R. Khuri; Haian Fu (Bioinform., 2018)

An Ensemble-based Active Learning for Breast Cancer Classification. - Sanghoon Lee 007; Mohamed Amgad; Mohamed Masoud; Rajasekaran Subramanian; David A. Gutman; Lee Cooper 001 (BIBM, 2019)

Joint region and nucleus segmentation for characterization of tumor infiltrating lymphocytes in breast cancer. - Mohamed Amgad; Anindya Sarkar; Chukka Srinivas; Rachel Redman; Simrath Ratra; Charles J. Bechert; Benjamin C. Calhoun; Karen Mrazeck; Uday Kurkure; Lee A. D. Cooper; Michael Barnes (Digital Pathology, 2019)

Structured crowdsourcing enables convolutional segmentation of histology images. - Mohamed Amgad; Habiba Elfandy; Hagar Hussein; Lamees A. Atteya; Mai A. T. Elsebaie; Lamia S. Abo Elnasr; Rokia Adel Sakr; Hazem S. E. Salem; Ahmed F. Ismail; Anas M. Saad; Joumana Ahmed; Maha A. T. Elsebaie; et al. (Bioinform., 2019)

Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization. - Pegah Khosravi; Ehsan Kazemi 001; Qiansheng Zhan; Jonas Malmsten; Marco Toschi; Pantelis Zisimopoulos; Alexandros Sigaras; Stuart Lavery; Lee A. D. Cooper; Cristina Hickman; Marcos Meseguer; Zev Rosenwaks; et al. (npj Digit. Medicine, 2019)

HistomicsML2.0: Fast interactive machine learning for whole slide imaging data. - Sanghoon Lee 007; Mohamed Amgad; Deepak Roy Chittajallu; Matt McCormick 001; Brian P. Pollack; Habiba Elfandy; Hagar Hussein; David A. Gutman; Lee A. D. Cooper (CoRR, 2020)

NuCLS: A scalable crowdsourcing, deep learning approach and dataset for nucleus classification, localization and segmentation. - Mohamed Amgad; Lamees A. Atteya; Hagar Hussein; Kareem Hosny Mohammed; Ehab Hafiz; Maha A. T. Elsebaie; Ahmed M. Alhusseiny; Mohamed Atef AlMoslemany; Abdelmagid M. Elmatboly; Philip A. Pappalardo; Rokia Adel Sakr; Pooya Mobadersany; et al. (CoRR, 2021)

A Histopathology Study Comparing Contrastive Semi-Supervised and Fully Supervised Learning. - Lantian Zhang; Mohamed Amgad; Lee A. D. Cooper (CoRR, 2021)

Explainable nucleus classification using Decision Tree Approximation of Learned Embeddings. - Mohamed Amgad; Lamees A. Atteya; Hagar Hussein; Kareem Hosny Mohammed; Ehab Hafiz; Maha A. T. Elsebaie; Pooya Mobadersany; David Manthey; David A. Gutman; Habiba Elfandy; Lee A. D. Cooper (Bioinform., 2022)

MONAI: An open-source framework for deep learning in healthcare. - M. Jorge Cardoso; Wenqi Li 001; Richard Brown 004; Nic Ma; Eric Kerfoot; Yiheng Wang; Benjamin Murray; Andriy Myronenko; Can Zhao 001; Dong Yang 005; Vishwesh Nath; Yufan He; et al. (CoRR, 2022)

Crowdsourcing Segmentation of Histopathological Images Using Annotations Provided by Medical Students. - Miguel López-Pérez; Pablo Morales-Álvarez; Lee A. D. Cooper; Rafael Molina 001; Aggelos K. Katsaggelos (AIME, 2023)

Deep learning to predict the proportion of positive cells in CMYC-stained tissue microarrays of diffuse large B-cell lymphoma. - Thomas E. Tavolara; M. Khalid Khan Niazi; David Jaye; Christopher Flowers; Lee Cooper 001; Metin N. Gurcan (Digital and Computational Pathology, 2023)

Deep Gaussian Processes for Classification With Multiple Noisy Annotators. Application to Breast Cancer Tissue Classification. - Miguel López-Pérez; Pablo Morales-Álvarez; Lee A. D. Cooper; Rafael Molina 001; Aggelos K. Katsaggelos (IEEE Access, 2023)

Learning from crowds for automated histopathological image segmentation. - Miguel López-Pérez; Pablo Morales-Álvarez; Lee A. D. Cooper; Christopher Felicelli; Jeffery A. Goldstein; Brian Vadasz; Rafael Molina 001; Aggelos K. Katsaggelos (Comput. Medical Imaging Graph., 2024)

BraTS-Path Challenge: Assessing Heterogeneous Histopathologic Brain Tumor Sub-regions. - Spyridon Bakas; Siddhesh P. Thakur; Shahriar Faghani; Mana Moassefi; Ujjwal Baid; Verena Chung; Sarthak Pati; Shubham Innani; Bhakti Baheti; Jake Albrecht; Alexandros Karargyris; Hasan Kassem; et al. (CoRR, 2024)

Novel Clinical-Grade Prostate Cancer Detection and Grading Model: Development and Prospective Validation Using Real World Data, with Performance Assessment on IHC Requested Cases. - Ramin Nateghi; Ruoji Zhou; Madeline Saft; Marina Schnauss; Clayton Neill; Ridwan Alam; Nicole Handa; Mitchell Huang; Eric V. Li; Jeffery A. Goldstein; Edward M. Schaeffer; Menatalla K. Nadim; et al. (CoRR, 2024)

Machine learning identification of maternal inflammatory response and histologic choroamnionitis from placental membrane whole slide images. - Abhishek Sharma; Ramin Nateghi; Marina Ayad; Lee A. D. Cooper; Jeffery A. Goldstein (CoRR, 2024)

Deep Learning for Fetal Inflammatory Response Diagnosis in the Umbilical Cord. - Marina A. Ayad; Ramin Nateghi; Abhishek Sharma; Lawrence Chillrud; Tilly Seesillapachai; Lee A. D. Cooper; Jeffery A. Goldstein (CoRR, 2024)

Focused active learning for histopathological image classification. - Arne Schmidt 005; Pablo Morales-Álvarez; Lee A. D. Cooper; Lee A. Newberg; Andinet Enquobahrie; Rafael Molina 001; Aggelos K. Katsaggelos (Medical Image Anal., 2024)

Using Variational Autoencoders for Out of Distribution Detection in Histological Multiple Instance Learning. - Francisco Javier Sáez-Maldonado; Luz García 001; Lee A. D. Cooper; Jeffery A. Goldstein; Rafael Molina 001; Aggelos K. Katsaggelos (IEEE Access, 2025)