Automatic segmentation of the left atrium from MR images via variational region growing with a moments-based shape prior.
The planning and evaluation of left atrial ablation procedures are commonly based on the segmentation of the left atrium, which is a challenging task due to large anatomical variations. In this paper, we propose an automatic approach for segmenting the left atrium from magnetic resonance imagery. The segmentation problem is formulated as a problem in variational region growing. In particular, the method starts locally by searching for a seed region of the left atrium from an MR slice. A global constraint is imposed by applying a shape prior to the left atrium represented by Zernike moments. The overall growing process is guided by the robust statistics of intensities from the seed region along with the shape prior to capture the entire atrial region. The robustness and accuracy of our approach are demonstrated by experimental results from 64 human MR images.
Liangjia
L
Zhu
Yi
Y
Gao
Anthony
A
Yezzi
Allen
A
Tannenbaum
D000465:Algorithms; D001185:Artificial Intelligence; D001281:Atrial Fibrillation / Q000628:therapy; D017115:Catheter Ablation; D006325:Heart Atria / Q000033:anatomy & histology* / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*