publication . Other literature type . Article . 2006

User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability

Rachel Gimpel Smith; Paul A. Yushkevich; Joseph Piven; Sean Ho; Guido Gerig; Heather Cody Hazlett; James C. Gee;

Open Access

Published: 01 Jul 2006

Publisher: Elsevier BV

Summary

Abstract

Active contour segmentation and its robust implementation using level set methods are well-established theoretical approaches that have been studied thoroughly in the image analysis literature. Despite the existence of these powerful segmentation methods, the needs of clinical research continue to be fulfilled, to a large extent, using slice-by-slice manual tracing. To bridge the gap between methodological advances and clinical routine, we developed an open source application called ITK-SNAP, which is intended to make level set segmentation easily accessible to a wide range of users, including those with little or no mathematical expertise. This paper describes ...

doi: 10.1016/j.neuroimage.2006.01.015

Subjects

free text keywords: Artificial intelligence, business.industry, business, Tracing, Computer vision, Segmentation, Inter-rater reliability, Computational anatomy, Scale-space segmentation, Machine learning, computer.software_genre, computer, Image segmentation, Active contour model, Level set, Computer science

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