Projects:LeftAtriumSegmentation
Back to Boston University Algorithms
Automatic Segmentation of Left Atrium using Variational Region Growing
Description
The planning and evaluation of left atrial ablation procedures is commonly based on the segmentation of the left atrium, which is a challenging task due to large anatomical variations. We propose an automatic approach for segmenting the left atrium from magnetic resonance imagery (MRI). 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 a given 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 whole atrial region.
The proposed method consists of two key steps: (1) search for a seed region of the LA from an image slice in the axial view. (2) explore the LA region using a variational region-growing process. A shape prior is employed to drive the growing process towards atrium-like shapes.
