198 citations · 270 across the 8 of their papers we have counts for
8 papers
A Petri Dish for Histopathology Image Analysis
Jerry Wei, Arief Suriawinata, Bing Ren +9
With the rise of deep learning, there has been increased interest in using neural networks for histopathology image analysis, a field that investigates the properties of biopsy or…
Development and Evaluation of a Deep Neural Network for Histologic Classification of Renal Cell Carcinoma on Biopsy and Surgical Resection Slides
Mengdan Zhu, Bing Ren, Ryland Richards +3
Renal cell carcinoma (RCC) is the most common renal cancer in adults. The histopathologic classification of RCC is essential for diagnosis, prognosis, and management of patients. R…
Learn like a Pathologist: Curriculum Learning by Annotator Agreement for Histopathology Image Classification
Jerry Wei, Arief Suriawinata, Bing Ren +10
Applying curriculum learning requires both a range of difficulty in data and a method for determining the difficulty of examples. In many tasks, however, satisfying these requireme…
Difficulty Translation in Histopathology Images
Jerry Wei, Arief Suriawinata, Xiaoying Liu +5
The unique nature of histopathology images opens the door to domain-specific formulations of image translation models. We propose a difficulty translation model that modifies color…
Generative Image Translation for Data Augmentation in Colorectal Histopathology Images
Jerry Wei, Arief Suriawinata, Louis Vaickus +4
We present an image translation approach to generate augmented data for mitigating data imbalances in a dataset of histopathology images of colorectal polyps, adenomatous tumors th…
Deep neural networks for automated classification of colorectal polyps on histopathology slides: A multi-institutional evaluation
Jason W. Wei, Arief A. Suriawinata, Louis J. Vaickus +10
Histological classification of colorectal polyps plays a critical role in both screening for colorectal cancer and care of affected patients. An accurate and automated algorithm fo…