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.
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Kronman, A., Joskowicz, L. (2013). Image Segmentation Errors Correction by Mesh Segmentation and Deformation. In: Mori, K., Sakuma, I., Sato, Y., Barillot, C., Navab, N. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013. MICCAI 2013. Lecture Notes in Computer Science, vol 8150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40763-5_26
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DOI: https://doi.org/10.1007/978-3-642-40763-5_26
Publisher Name: Springer, Berlin, Heidelberg
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