Delineation of liver tumors from CT scans using spectral clustering with out-of-sample extension and multi-windowing

Jiayin Zhou, Weimin Huang, Wei Xiong, Wenyu Chen, Sudhakar K Venkatesh, Qi Tian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Accurate extraction of live tumors from CT data is important for disease management. In this study, an algorithm based on spectral clustering with out-of-sample extension is developed for the semi-automated delineation of liver tumors from 3D CT scans. In this method, spatial information is incorporated into a similarity metric together with low-level image features. A trick of out-of-sample extension is performed to reduce the computational burden in eigen-decomposition for a large matrix. Experimental results show that the developed method using multi-windowing feature obtained better results than using only the original data-depth and the support vector machine method, with a sensitivity of 0.77 and a Jaccard similarity measure of 0.70.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages246-254
Number of pages9
Volume7601 LNCS
DOIs
StatePublished - 2012
Event4th International Workshop on Computational and Clinical Applications in Abdominal Imaging, Held in Conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012 - Nice, France
Duration: Oct 1 2012Oct 1 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7601 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other4th International Workshop on Computational and Clinical Applications in Abdominal Imaging, Held in Conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012
CountryFrance
CityNice
Period10/1/1210/1/12

Fingerprint

Spectral Clustering
Computerized tomography
Liver
Tumors
Tumor
Data Depth
Support vector machines
Spatial Information
Decomposition
Similarity Measure
Support Vector Machine
Decompose
Metric
Experimental Results

Keywords

  • CT
  • out-of-sample extension
  • Spectral clustering
  • tumor delineation

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Zhou, J., Huang, W., Xiong, W., Chen, W., Venkatesh, S. K., & Tian, Q. (2012). Delineation of liver tumors from CT scans using spectral clustering with out-of-sample extension and multi-windowing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7601 LNCS, pp. 246-254). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7601 LNCS). https://doi.org/10.1007/978-3-642-33612-6_26

Delineation of liver tumors from CT scans using spectral clustering with out-of-sample extension and multi-windowing. / Zhou, Jiayin; Huang, Weimin; Xiong, Wei; Chen, Wenyu; Venkatesh, Sudhakar K; Tian, Qi.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7601 LNCS 2012. p. 246-254 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7601 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhou, J, Huang, W, Xiong, W, Chen, W, Venkatesh, SK & Tian, Q 2012, Delineation of liver tumors from CT scans using spectral clustering with out-of-sample extension and multi-windowing. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7601 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7601 LNCS, pp. 246-254, 4th International Workshop on Computational and Clinical Applications in Abdominal Imaging, Held in Conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012, Nice, France, 10/1/12. https://doi.org/10.1007/978-3-642-33612-6_26
Zhou J, Huang W, Xiong W, Chen W, Venkatesh SK, Tian Q. Delineation of liver tumors from CT scans using spectral clustering with out-of-sample extension and multi-windowing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7601 LNCS. 2012. p. 246-254. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-33612-6_26
Zhou, Jiayin ; Huang, Weimin ; Xiong, Wei ; Chen, Wenyu ; Venkatesh, Sudhakar K ; Tian, Qi. / Delineation of liver tumors from CT scans using spectral clustering with out-of-sample extension and multi-windowing. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7601 LNCS 2012. pp. 246-254 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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