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Image Segmentation Errors Correction by Mesh Segmentation and Deformation
Achia Kronman and Leo Joskowicz
School of Eng. and Computer Science, The Hebrew Univ. of Jerusalem, Israelachiak@cs.huji.ac.il
Abstract. 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.
LNCS 8150, p. 206 ff.
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© Springer-Verlag Berlin Heidelberg 2013