176 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Marquette UniversityUS6 papers
- Indiana University School of Medicine3 papers
- Queen Mary University of LondonGB3 papers
- The University of SydneyAU3 papers
- University Hospital BonnDE3 papers
- University of MichiganUS3 papers
- University of TorontoCA3 papers
- Aichi Medical UniversityJP2 papers
- Artificial Intelligence in Medicine (Canada)CA2 papers
- Baylor College of MedicineUS2 papers
- Bostwick LaboratoriesUS2 papers
- Cleveland ClinicUS2 papers
6 papers · 1 filter
Breast Cancer Classification in Deep Ultraviolet Fluorescence Images Using a Patch-Level Vision Transformer Framework
Pouya Afshin, David Helminiak, Tongtong Lu +5
Breast-conserving surgery (BCS) aims to completely remove malignant lesions while maximizing healthy tissue preservation. Intraoperative margin assessment is essential to achieve a…
The Federated Tumor Segmentation (FeTS) Challenge
Sarthak Pati, Ujjwal Baid, Maximilian Zenk +29
This manuscript describes the first challenge on Federated Learning, namely the Federated Tumor Segmentation (FeTS) challenge 2021. International challenges have become the standar…
Weakly-supervised Learning for Single-step Quantitative Susceptibility Mapping
Juan Liu, Kevin M Koch
Quantitative susceptibility mapping (QSM) utilizes MRI phase information to estimate tissue magnetic susceptibility. The generation of QSM requires solving ill-posed background fie…
Artificial Intelligence Assistance Significantly Improves Gleason Grading of Prostate Biopsies by Pathologists
Wouter Bulten, Maschenka Balkenhol, Jean-Joël Awoumou Belinga +17
While the Gleason score is the most important prognostic marker for prostate cancer patients, it suffers from significant observer variability. Artificial Intelligence (AI) systems…
A fully 3D multi-path convolutional neural network with feature fusion and feature weighting for automatic lesion identification in brain MRI images
Yunzhe Xue, Meiyan Xie, Fadi G. Farhat +5
We propose a fully 3D multi-path convolutional network to predict stroke lesions from 3D brain MRI images. Our multi-path model has independent encoders for different modalities co…
Iterative annotation to ease neural network training: Specialized machine learning in medical image analysis
Brendon Lutnick, Brandon Ginley, Darshana Govind +7
Neural networks promise to bring robust, quantitative analysis to medical fields, but adoption is limited by the technicalities of training these networks. To address this translat…