1 code implementation • 9 Apr 2023 • James M. Dolezal, Sara Kochanny, Emma Dyer, Andrew Srisuwananukorn, Matteo Sacco, Frederick M. Howard, Anran Li, Prajval Mohan, Alexander T. Pearson
Deep learning methods have emerged as powerful tools for analyzing histopathological images, but current methods are often specialized for specific domains and software environments, and few open-source options exist for deploying models in an interactive interface.
Histopathological Image Classification Histopathological Segmentation +5
2 code implementations • 12 Nov 2022 • James M. Dolezal, Rachelle Wolk, Hanna M. Hieromnimon, Frederick M. Howard, Andrew Srisuwananukorn, Dmitry Karpeyev, Siddhi Ramesh, Sara Kochanny, Jung Woo Kwon, Meghana Agni, Richard C. Simon, Chandni Desai, Raghad Kherallah, Tung D. Nguyen, Jefree J. Schulte, Kimberly Cole, Galina Khramtsova, Marina Chiara Garassino, Aliya N. Husain, Huihua Li, Robert Grossman, Nicole A. Cipriani, Alexander T. Pearson
Artificial intelligence methods including deep neural networks (DNN) can provide rapid molecular classification of tumors from routine histology with accuracy that matches or exceeds human pathologists.