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20162023
most citedDeep Learning-based Computational Pathology Predicts Origins for Cancers of Unknown Primary

645 citations · 1.5k across the 36 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

cs.CV2019★ 11 cited

Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis

Richard J. Chen, Ming Y. Lu, Jingwen Wang +4

Cancer diagnosis, prognosis, and therapeutic response predictions are based on morphological information from histology slides and molecular profiles from genomic data. However, mo…

cs.CV2019★ 6 cited

Weakly Supervised Prostate TMA Classification via Graph Convolutional Networks

Jingwen Wang, Richard J. Chen, Ming Y. Lu +2

Histology-based grade classification is clinically important for many cancer types in stratifying patients distinct treatment groups. In prostate cancer, the Gleason score is a gra…

cs.CV2019★ 33 cited

Semi-Supervised Histology Classification using Deep Multiple Instance Learning and Contrastive Predictive Coding

Ming Y. Lu, Richard J. Chen, Jingwen Wang +2

Convolutional neural networks can be trained to perform histology slide classification using weak annotations with multiple instance learning (MIL). However, given the paucity of l…

eess.IV2019★ 21 cited

SLAM Endoscopy enhanced by adversarial depth prediction

Richard J. Chen, Taylor L. Bobrow, Thomas Athey +2

Medical endoscopy remains a challenging application for simultaneous localization and mapping (SLAM) due to the sparsity of image features and size constraints that prevent direct…

eess.IV2019

GANPOP: Generative Adversarial Network Prediction of Optical Properties from Single Snapshot Wide-field Images

Mason T. Chen, Faisal Mahmood, Jordan A. Sweer +1

We present a deep learning framework for wide-field, content-aware estimation of absorption and scattering coefficients of tissues, called Generative Adversarial Network Prediction…

cs.CV2019★ 5 cited

Structured Prediction using cGANs with Fusion Discriminator

Faisal Mahmood, Wenhao Xu, Nicholas J. Durr +2

We propose the fusion discriminator, a single unified framework for incorporating conditional information into a generative adversarial network (GAN) for a variety of distinct stru…