- Title
- Automatic liver parenchyma segmentation from abdominal CT images using support vector machines
- Creator
- Luo, Suhuai; Hu, Qingmao; He, Xiangjian; Li, Jiaming; Jin, Jesse S.; Park, Mira
- Relation
- ICME International Conference on Complex Medical Engineering, 2009 (ICME 2009). Proceedings of the 2009 ICME International Conference on Complex Medical Engineering, ICME 2009 (Tempe, AZ 9-11 April, 2009)
- Publisher Link
- http://dx.doi.org/10.1109/ICCME.2009.4906625
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- conference paper
- Date
- 2009
- Description
- This paper presents an automatic liver parenchyma segmentation algorithm that can segment liver in abdominal CT images. There are three major steps in the proposed approach. Firstly, a texture analysis is applied to input abdominal CT images to extract pixel level features. In this step, wavelet coefficients are used as texture descriptors. Secondly, support vector machines (SVMs) are implemented to classify the data into pixel-wised liver area or non-liver area. Finally, integrated morphological operations are designed to remove noise and finally delineate the liver. Our unique contributions to liver segmentation are twofold: one is that it has been proved through experiments that wavelet features present good classification result when SVMs are used; the other is that the combination of morphological operations with the pixel-wised SVM classifier can delineate volumetric liver accurately. The algorithm can be used in an advanced computer-aided liver disease diagnosis and liver surgical planning system. Examples of applying the proposed algorithm on real CT data are presented with performance validation based on the comparison between the automatically segmented results and manually segmented ones.
- Subject
- abdominal CT images; automatic liver parenchyma segmentation algorithm; computer-aided liver disease diagnosis; computerised tomography; data classification; image texture analysis; liver surgical planning systems; support vector machines; wavelet coefficients
- Identifier
- http://hdl.handle.net/1959.13/919095
- Identifier
- uon:8772
- Identifier
- ISBN:9781424433162
- Rights
- Copyright © 2009 IEEE. Reprinted from the Proceedings of the 2009 ICME International Conference on Complex Medical Engineering, ICME 2009. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of University of Newcastle's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
- Language
- eng
- Full Text
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