2 papers
physics.med-ph2026
Improving Clinical Target Volume Segmentation Accuracy using Anatomical Priors and Active Learning for the AGITG TOPGEAR Clinical Trial
Phillip Chlap, Mark Lee, Trevor Leong +11
Training deep learning-based medical image segmentation models is challenging with limited curated datasets. For AGITG TOPGEAR, a gastric cancer trial, the Clinical Target Volume (…
eess.IV2024
Evaluating the Impact of Sequence Combinations on Breast Tumor Segmentation in Multiparametric MRI
Hang Min, Gorane Santamaria Hormaechea, Prabhakar Ramachandran +1
Multiparametric magnetic resonance imaging (mpMRI) is a key tool for assessing breast cancer progression. Although deep learning has been applied to automate tumor segmentation in…