Volumetric image segmentation methods often produce delineations of anatomical structures and pathologies that require user modifications. We present a new method for the correction of segmentation errors. Given an initial geometrical mesh, our method semi automatically identifies the mesh vertices in erroneous regions with min-cut segmentation. It then deforms the mesh by correcting its vertex coordinates with Laplace deformation based on local geometrical properties. The key advantages of our method are that: 1) it supports fast user interaction on a single surface rendered 2D view; 2) its parameters values are fixed to the same value for all cases; 3) it is independent of the initial segmentation method, and; 4) it is applicable to a variety of anatomical structures and pathologies. Experimental evaluation on 44 initial segmentations of kidney and kidney vessels from CT scans show an improvement of 83% and 75% in the average surface distance and the volume overlap error between the initial and the corrected segmentations with respect to the ground-truth. © 2013 Springer-Verlag.
CITATION STYLE
Kronman, A., & Joskowicz, L. (2013). Image segmentation errors correction by mesh segmentation and deformation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8150 LNCS, pp. 206–213). https://doi.org/10.1007/978-3-642-40763-5_26
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