33 citations · 134 across the 18 of their papers we have counts for
6 papers · 1 filter
Multimodal Whole Slide Foundation Model for Pathology
Tong Ding, Sophia J. Wagner, Andrew H. Song +20
The field of computational pathology has been transformed with recent advances in foundation models that encode histopathology region-of-interests (ROIs) into versatile and transfe…
Artificial Intelligence for Digital and Computational Pathology
Andrew H. Song, Guillaume Jaume, Drew F. K. Williamson +4
Advances in digitizing tissue slides and the fast-paced progress in artificial intelligence, including deep learning, have boosted the field of computational pathology. This field…
Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks
Richard J. Chen, Ming Y. Lu, Muhammad Shaban +4
Cancer prognostication is a challenging task in computational pathology that requires context-aware representations of histology features to adequately infer patient survival. Desp…
Deep Learning-based Frozen Section to FFPE Translation
Kutsev Bengisu Ozyoruk, Sermet Can, Guliz Irem Gokceler +12
Frozen sectioning (FS) is the preparation method of choice for microscopic evaluation of tissues during surgical operations. The high speed of the procedure allows pathologists to…
Federated Learning for Computational Pathology on Gigapixel Whole Slide Images
Ming Y. Lu, Dehan Kong, Jana Lipkova +5
Deep Learning-based computational pathology algorithms have demonstrated profound ability to excel in a wide array of tasks that range from characterization of well known morpholog…
Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Images
Ming Y. Lu, Drew F. K. Williamson, Tiffany Y. Chen +3
The rapidly emerging field of computational pathology has the potential to enable objective diagnosis, therapeutic response prediction and identification of new morphological featu…