Efficiently Writing and Visualizing Many-Dimension Large Images.
Haley, Anne, David Manthey, Lee Cooper, and David Gutman. 2024. “Poster Presentations: Efficiently Writing and Visualizing Many-Dimension Large Images.” Digital Pathology & AI Congress, May 7-8, 2024. Poster2024DigPathAI.pdf
A User-Friendly Tool for Cloud-Based Whole Slide Image Segmentation with Examples from Renal Histopathology.
Lutnick, Brendon, David Manthey, Jan U. Becker, Brandon Ginley, Katharina Moos, Jonathan E. Zuckerman, Luis Rodrigues, et al. 2022. “A User-Friendly Tool for Cloud-Based Whole Slide Image Segmentation with Examples from Renal Histopathology.” Communications Medicine. Springer Science and Business Media LLC. https://doi.org/10.1038/s43856-022-00138-z
DOI: 10.1038/s43856-022-00138-z
PodoCount: A Robust, Fully Automated, Whole-Slide Podocyte Quantification Tool.
Santo, Briana A., Darshana Govind, Parnaz Daneshpajouhnejad, Xiaoping Yang, Xiaoxin X. Wang, Komuraiah Myakala, Bryce A. Jones, et al. 2022. “PodoCount: A Robust, Fully Automated, Whole-Slide Podocyte Quantification Tool.” Kidney International Reports. Elsevier BV. https://doi.org/10.1016/j.ekir.2022.03.004
DOI: 10.1016/j.ekir.2022.03.004
A Tool for Federated Training of Segmentation Models on Whole Slide Images.
Lutnick, Brendon, David Manthey, Jan U. Becker, Jonathan E. Zuckerman, Luis Rodrigues, Kuang-Yu Jen, and Pinaki Sarder. 2022. “A Tool for Federated Training of Segmentation Models on Whole Slide Images.” Journal of Pathology Informatics. Elsevier BV. https://doi.org/10.1016/j.jpi.2022.100101
DOI: 10.1016/j.jpi.2022.100101
Explainable Nucleus Classification Using Decision Tree Approximation of Learned Embeddings
Amgad, Mohamed, LameesA Atteya, Hagar Hussein, Kareem Hosny Mohammed, Ehab Hafiz, Maha A T Elsebaie, Pooya Mobadersany, et al. 2021. “Explainable Nucleus Classification Using Decision Tree Approximation of Learned Embeddings.” Edited by Jinbo Xu. Bioinformatics, September. https://doi.org/10.1093/bioinformatics/btab670
DOI: 10.1093/bioinformatics/btab670
PodoSighter: A Cloud-Based Tool for Label-Free Podocyte Detection in Kidney Whole Slide Images
Govind, Darshana, Jan Becker, Jeffrey Miecznikowski, Avi Rosenberg, Julien Dang, Pierre Louis Tharaux, Rabi Yacoub, et al. 2021. “PodoSighter: A Cloud-Based Tool for Label-Free Podocyte Detection in Kidney Whole Slide Images.” Journal of the American Society of Nephrology, September, ASN.2021050630. https://doi.org/10.1681/asn.2021050630
DOI: 10.1681/asn.2021050630
User Friendly, Cloud Based, Whole Slide Image Segmentation.
Lutnick, Brendon, Avinash Kammardi Shashiprakash, David Manthey, and Pinaki Sarder. 2021. “User Friendly, Cloud Based, Whole Slide Image Segmentation.” In Medical Imaging 2021: Digital Pathology, edited by John E. Tomaszewski and Aaron D. Ward. SPIE. https://doi.org/10.1117/12.2581383
DOI: 10.1117/12.2581383
A Distributed System Improves Inter-Observer and AI Concordance in Annotating Interstitial Fibrosis and Tubular Atrophy.
Kammardi Shashiprakash, Avinash, Brendon Lutnick, Brandon Ginley, Darshana Govind, Nicholas Lucarelli, Kuang-Yu Jen, Avi Z. Rosenberg, et al. 2021. “A Distributed System Improves Inter-Observer and AI Concordance in Annotating Interstitial Fibrosis and Tubular Atrophy.” In Medical Imaging 2021: Digital Pathology, edited by John E. Tomaszewski and Aaron D. Ward. SPIE. https://doi.org/10.1117/12.2581789
DOI: 10.1117/12.2581789
Machine-based detection and classification for bone marrow aspirate differential counts - initial development focusing on nonneoplastic cells.
Chandradevan, Ramraj, Ahmed A. Aljudi, Bradley R. Drumheller, Nilakshan Kunananthaseelan, Mohamed Amgad, David A. Gutman, Lee A. D. Cooper, and David L. Jaye. “Machine-Based Detection and Classification for Bone Marrow Aspirate Differential Counts: Initial Development Focusing on Nonneoplastic Cells.” Laboratory Investigation 100, no. 1 (September 30, 2019): 98–109. https://doi.org/10.1038/s41374-019-0325-7
DOI: 10.1038/s41374-019-0325-7
Phosphoinositide 3-Kinase Signaling Can Modulate MHC Class I and II Expression.
Chandrasekaran, Sanjay, Maiko Sasaki, Christopher D. Scharer, Haydn T. Kissick, Dillon G. Patterson, Kelly R. Magliocca, John T. Seykora, et al. “Phosphoinositide 3-Kinase Signaling Can Modulate MHC Class I and II Expression.” Molecular Cancer Research 17, no. 12 (September 23, 2019): 2395–2409. https://doi.org/10.1158/1541-7786.mcr-19-0545
DOI: 10.1158/1541-7786.MCR-19-0545
Structured crowdsourcing enables convolutional segmentation of histology images.
Amgad, Mohamed, Habiba Elfandy, Hagar Hussein, Lamees A Atteya, Mai A T Elsebaie, Lamia S Abo Elnasr, Rokia A Sakr, et al. “Structured Crowdsourcing Enables Convolutional Segmentation of Histology Images.” Edited by Robert Murphy. Bioinformatics 35, no. 18 (February 6, 2019): 3461–67. https://doi.org/10.1038/s41374-019-0325-7
DOI: 10.1093/bioinformatics/btz083
Multi-faceted computational assessment of risk and progression in oligodendroglioma implicates NOTCH and PI3K pathways.
Halani, Sameer H., Safoora Yousefi, Jose Velazquez Vega, Michael R. Rossi, Zheng Zhao, Fatemeh Amrollahi, Chad A. Holder, et al. “Multi-Faceted Computational Assessment of Risk and Progression in Oligodendroglioma Implicates NOTCH and PI3K Pathways.” Npj Precision Oncology 2, no. 1 (November 6, 2018). https://doi.org/10.1038/s41698-018-0067-9
DOI: 10.1038/s41698-018-0067-9
PanCancer insights from The Cancer Genome Atlas - the pathologist's perspective.
Cooper, Lee AD, Elizabeth G Demicco, Joel H Saltz, Reid T Powell, Arvind Rao, and Alexander J Lazar. “PanCancer Insights from The Cancer Genome Atlas: The Pathologist’s Perspective.” The Journal of Pathology 244, no. 5 (February 22, 2018): 512–24. https://doi.org/10.1002/path.5028
DOI: 10.1002/path.5028
Predicting cancer outcomes from histology and genomics using convolutional networks.
Mobadersany, Pooya, Safoora Yousefi, Mohamed Amgad, David A. Gutman, Jill S. Barnholtz-Sloan, José E. Velázquez Vega, Daniel J. Brat, and Lee A. D. Cooper. “Predicting Cancer Outcomes from Histology and Genomics Using Convolutional Networks.” Proceedings of the National Academy of Sciences 115, no. 13 (March 12, 2018): E2970–79. https://doi.org/10.1073/pnas.1717139115
DOI: 10.1073/pnas.1717139115
Informatics Approaches to Address New Challenges in the Classification of Lymphoid Malignancies.
Jordan, Jacob, Jordan S. Goldstein, David L. Jaye, Metin Gurcan, Christopher R. Flowers, and Lee A.D. Cooper. “Informatics Approaches to Address New Challenges in the Classification of Lymphoid Malignancies.” JCO Clinical Cancer Informatics, no. 2 (December 2018): 1–9. https://doi.org/10.1200/cci.17.00039
DOI: 10.1200/CCI.17.00039
Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas.
Abeshouse, Adam, Clement Adebamowo, Sally N. Adebamowo, Rehan Akbani, Teniola Akeredolu, Adrian Ally, Matthew L. Anderson, et al. “Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas.” Cell 171, no. 4 (November 2017): 950–965.e28. https://doi.org/10.1016/j.cell.2017.10.014
DOI: 10.1016/j.cell.2017.10.014
The Digital Slide Archive - A Software Platform for Management, Integration, and Analysis of Histology for Cancer Research.
Gutman, David A., Mohammed Khalilia, Sanghoon Lee, Michael Nalisnik, Zach Mullen, Jonathan Beezley, Deepak R. Chittajallu, David Manthey, and Lee A.D. Cooper. “The Digital Slide Archive: A Software Platform for Management, Integration, and Analysis of Histology for Cancer Research.” Cancer Research 77, no. 21 (October 31, 2017): e75–78. https://doi.org/10.1158/0008-5472.can-17-0629
DOI: 10.1158/0008-5472.CAN-17-0629
Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma.
Ceccarelli, Michele, Floris P. Barthel, Tathiane M. Malta, Thais S. Sabedot, Sofie R. Salama, Bradley A. Murray, Olena Morozova, et al. “Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma.” Cell 164, no. 3 (January 2016): 550–63. https://doi.org/10.1016/j.cell.2015.12.028
DOI: 10.1016/j.cell.2015.12.028
Novel genotype-phenotype associations in human cancers enabled by advanced molecular platforms and computational analysis of whole slide images.
Cooper, Lee AD, Jun Kong, David A Gutman, William D Dunn, Michael Nalisnik, and Daniel J Brat. “Novel Genotype-Phenotype Associations in Human Cancers Enabled by Advanced Molecular Platforms and Computational Analysis of Whole Slide Images.” Laboratory Investigation 95, no. 4 (January 19, 2015): 366–76. https://doi.org/10.1038/labinvest.2014.153
DOI: 10.1038/labinvest.2014.153
Cancer Digital Slide Archive - an informatics resource to support integrated in silico analysis of TCGA pathology data.
Gutman, David A, Jake Cobb, Dhananjaya Somanna, Yuna Park, Fusheng Wang, Tahsin Kurc, Joel H Saltz, Daniel J Brat, Lee A D Cooper, and Jun Kong. “Cancer Digital Slide Archive: An Informatics Resource to Support Integrated in Silico Analysis of TCGA Pathology Data.” Journal of the American Medical Informatics Association 20, no. 6 (November 2013): 1091–98. https://doi.org/10.1136/amiajnl-2012-001469
DOI: 10.1136/amiajnl-2012-001469