16 citations · 26 across the 12 of their papers we have counts for
3 papers · 2 filters
MRISegmentator-Abdomen: A Fully Automated Multi-Organ and Structure Segmentation Tool for T1-weighted Abdominal MRI
Yan Zhuang, Tejas Sudharshan Mathai, Pritam Mukherjee +6
Background: Segmentation of organs and structures in abdominal MRI is useful for many clinical applications, such as disease diagnosis and radiotherapy. Current approaches have foc…
Deep Learning Segmentation of Ascites on Abdominal CT Scans for Automatic Volume Quantification
Benjamin Hou, Sung-Won Lee, Jung-Min Lee +4
Purpose: To evaluate the performance of an automated deep learning method in detecting ascites and subsequently quantifying its volume in patients with liver cirrhosis and ovarian…
Shadow and Light: Digitally Reconstructed Radiographs for Disease Classification
Benjamin Hou, Qingqing Zhu, Tejas Sudarshan Mathai +3
In this paper, we introduce DRR-RATE, a large-scale synthetic chest X-ray dataset derived from the recently released CT-RATE dataset. DRR-RATE comprises of 50,188 frontal Digitally…