19 citations · 23 across the 2 of their papers we have counts for
3 papers
Semi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI
Syed Muhammad Anwar, Ismail Irmakci, Drew A. Torigian +5
Segmentation of thigh tissues (muscle, fat, inter-muscular adipose tissue (IMAT), bone, and bone marrow) from magnetic resonance imaging (MRI) scans is useful for clinical and rese…
INN: Inflated Neural Networks for IPMN Diagnosis
Rodney LaLonde, Irene Tanner, Katerina Nikiforaki +5
Intraductal papillary mucinous neoplasm (IPMN) is a precursor to pancreatic ductal adenocarcinoma. While over half of patients are diagnosed with pancreatic cancer at a distant sta…
Context Driven Label Fusion for segmentation of Subcutaneous and Visceral Fat in CT Volumes
Sarfaraz Hussein, Aileen Green, Arjun Watane +3
Quantification of adipose tissue (fat) from computed tomography (CT) scans is conducted mostly through manual or semi-automated image segmentation algorithms with limited efficacy.…