Ontology highlight
ABSTRACT:
SUBMITTER: Jiang J
PROVIDER: S-EPMC6169798 | biostudies-literature | 2018 Sep
REPOSITORIES: biostudies-literature
Jiang Jue J Hu Yu-Chi YC Tyagi Neelam N Zhang Pengpeng P Rimner Andreas A Mageras Gig S GS Deasy Joseph O JO Veeraraghavan Harini H
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention 20180901
We present an adversarial domain adaptation based deep learning approach for automatic tumor segmentation from T2-weighted MRI. Our approach is composed of two steps: (i) a tumor-aware unsupervised cross-domain adaptation (CT to MRI), followed by (ii) semi-supervised tumor segmentation using Unet trained with synthesized and limited number of original MRIs. We introduced a novel target specific loss, called tumor-aware loss, for unsupervised cross-domain adaptation that helps to preserve tumors ...[more]