DIKUL - logo
E-viri
Celotno besedilo
Odprti dostop
  • Qiao, Mengyun; Wang, Yuanyuan; Rob J van der Geest; Qian Tao

    arXiv (Cornell University), 10/2018
    Paper, Journal Article

    This paper presents a fully automated method to segment the complex left atrial (LA) cavity, from 3D Gadolinium-enhanced magnetic resonance imaging (GE-MRI) scans. The proposed method consists of four steps: (1) preprocessing to convert the original GE-MRI to a probability map, (2) atlas selection to match the atlases to the target image, (3) multi-atlas registration and fusion, and (4) level-set refinement. The method was evaluated on the datasets provided by the MICCAI 2018 STACOM Challenge with 100 dataset for training. Compared to manual annotation, the proposed method achieved an average Dice overlap index of 0.88.