Paper Info
Title
Efficient Semiautomatic Segmentation of 3D Objects in Medical Images
Abstract
We present a fast and accurate tool for semiautomatic seg- mentation of volumetric medical images based on the live wire algorithm, shape-based interpolation and a new optimization method. While the user-steered live wire algorithm represents an efficient, precise and reproducible method for interactive segmentation of selected two- dimensional images, the shape-based interpolation allows the automatic approximation of contours on slices between user-defined boundaries. The combination of both methods leads to accurate segmentations with significantly reduced user interaction time. Moreover, the subsequent au- tomated optimization of the interpolated object contours results in a bet- ter segmentation quality or can be used to extend the distances between user-segmented images and for a further reduction of interaction time. Experiments were carried out on hepatic computer tomographies from three different clinics. The results of the segmentation of liver parenchyma have shown that the user interaction time can be reduced more than 60% by the combination of shape-based interpolation and our optimization method with volume deviations in the magnitude of inter-user differ- ences.
Year
DOI
Venue
2000
10.1007/978-3-540-40899-4_19
MICCAI
Keywords
Field
DocType
medical images,efficient semiautomatic segmentation,computed tomography
Active contour model,Computer vision,Scale-space segmentation,Pattern recognition,Computer science,Segmentation,Interpolation,Segmentation-based object categorization,Image segmentation,Artificial intelligence
Conference
Volume
ISSN
ISBN
1935
0302-9743
3-540-41189-5
Citations 
PageRank 
References 
70
6.51
13
Authors
3
Name
Order
Citations
PageRank
Andrea Schenk131031.12
P M Prause215818.01
Heinz-otto Peitgen31030114.91