Segmentation of the Liver using a 3D Statistical Shape Model
Please always quote using this URN: urn:nbn:de:0297-zib-7847
- This paper presents an automatic approach for segmentation of the liver from computer tomography (CT) images based on a 3D statistical shape model. Segmentation of the liver is an important prerequisite in liver surgery planning. One of the major challenges in building a 3D shape model from a training set of segmented instances of an object is the determination of the correspondence between different surfaces. We propose to use a geometric approach that is based on minimizing the distortion of the correspondence mapping between two different surfaces. For the adaption of the shape model to the image data a profile model based on the grey value appearance of the liver and its surrounding tissues in contrast enhanced CT data was developed. The robustness of this method results from a previous nonlinear diffusion filtering of the image data. Special focus is turned to the quantitative evaluation of the segmentation process. Several different error measures are discussed and implemented in a study involving more than 30 livers.
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| Author: | Hans LameckerORCiD, Thomas Lange, Martin Seebass |
|---|---|
| Document Type: | ZIB-Report |
| Tag: | 3D Correspondence Problem; Diffusion Filtering; Geometric Distortion; Model-Based Segmentation; Statistical Shape Model; Surface Distance |
| MSC-Classification: | 68-XX COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area) / 68Uxx Computing methodologies and applications / 68U01 General |
| CCS-Classification: | I. Computing Methodologies / I.4 IMAGE PROCESSING AND COMPUTER VISION (REVISED) / I.4.6 Segmentation |
| I. Computing Methodologies / I.5 PATTERN RECOGNITION / I.5.1 Models | |
| Date of first Publication: | 2004/04/02 |
| Series (Serial Number): | ZIB-Report (04-09) |
| ZIB-Reportnumber: | 04-09 |
