12 citations · 18 across the 3 of their papers we have counts for
5 papers
Deep Learning-Based Sparse Whole-Slide Image Analysis for the Diagnosis of Gastric Intestinal Metaplasia
Jon Braatz, Pranav Rajpurkar, Stephanie Zhang +2
In recent years, deep learning has successfully been applied to automate a wide variety of tasks in diagnostic histopathology. However, fast and reliable localization of small-scal…
Learning domain-agnostic visual representation for computational pathology using medically-irrelevant style transfer augmentation
Rikiya Yamashita, Jin Long, Snikitha Banda +2
Suboptimal generalization of machine learning models on unseen data is a key challenge which hampers the clinical applicability of such models to medical imaging. Although various…
Analysis Of Multi Field Of View Cnn And Attention Cnn On H&E Stained Whole-slide Images On Hepatocellular Carcinoma
Mehmet Burak Sayıcı, Rikiya Yamashita, Jeanne Shen
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. Whole-slide imaging which is a method of scanning glass slides have been employed for diagnosis…
Deep Learning for the Digital Pathologic Diagnosis of Cholangiocarcinoma and Hepatocellular Carcinoma: Evaluating the Impact of a Web-based Diagnostic Assistant
Bora Uyumazturk, Amirhossein Kiani, Pranav Rajpurkar +17
While artificial intelligence (AI) algorithms continue to rival human performance on a variety of clinical tasks, the question of how best to incorporate these algorithms into clin…
Plexus Convolutional Neural Network (PlexusNet): A novel neural network architecture for histologic image analysis
Okyaz Eminaga, Mahmoud Abbas, Christian Kunder +5
Different convolutional neural network (CNN) models have been tested for their application in histological image analyses. However, these models are prone to overfitting due to the…