A new robust active shape model formulation for cardiac MRI segmentation


The 3D segmentation of the left ventricle (LV) in cardiac MRI is a challenging problem, due to the presence of other anatomical structures and artifacts (outliers) around the LV. In this paper, a new formulation of a Robust Active Shape Model (RASM) is presented that is able to deal with those outliers. Instead of using the traditional one-to-one mapping of edge points and model points to compute the shape model parameters, the proposed approach uses a one-to-many mapping strategy and groups these edge points into edge segments (strokes). Then, a probabilistic framework provides a robust estimation of the model parameters, in which the influence in the segmentation of the unreliable outliers is reduced. The proposed method was tested on a public dataset comprising 660 volumes. The results indicate that this methodology provides accurate segmentations that are competitive with other state-of-the art methods.

DOI: 10.1109/ICIP.2016.7533133

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@article{Santiago2016ANR, title={A new robust active shape model formulation for cardiac MRI segmentation}, author={Carlos Santiago and Jacinto C. Nascimento and Jorge S. Marques}, journal={2016 IEEE International Conference on Image Processing (ICIP)}, year={2016}, pages={4112-4115} }