1.1k citations · 3.1k across the 15 of their papers we have counts for
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A Pathologist-Annotated Dataset for Validating Artificial Intelligence: A Project Description and Pilot Study
Sarah N Dudgeon, Si Wen, Matthew G Hanna +19
Purpose: In this work, we present a collaboration to create a validation dataset of pathologist annotations for algorithms that process whole slide images (WSIs). We focus on data…
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos +6
Since its renaissance, deep learning has been widely used in various medical imaging tasks and has achieved remarkable success in many medical imaging applications, thereby propell…
Can tumor location on pre-treatment MRI predict likelihood of pseudo-progression versus tumor recurrence in Glioblastoma? A feasibility study
Marwa Ismail, Virginia Hill, Volodymyr Statsevych +9
A significant challenge in Glioblastoma (GBM) management is identifying pseudo-progression (PsP), a benign radiation-induced effect, from tumor recurrence, on routine imaging follo…
MRQy: An Open-Source Tool for Quality Control of MR Imaging Data
Amir Reza Sadri, Andrew Janowczyk, Ren Zou +6
We sought to develop a quantitative tool to quickly determine relative differences in MRI volumes both within and between large MR imaging cohorts (such as available in The Cancer…
Deep learning-based prediction of response to HER2-targeted neoadjuvant chemotherapy from pre-treatment dynamic breast MRI: A multi-institutional validation study
Nathaniel Braman, Mohammed El Adoui, Manasa Vulchi +10
Predicting response to neoadjuvant therapy is a vexing challenge in breast cancer. In this study, we evaluate the ability of deep learning to predict response to HER2-targeted neo-…