A Fuzzy-C-Means clustering algorithm for a volumetric analysis of paranasal sinus and nasal cavity cancers

K. Passera; P. Potepan; E. Setti; D. Vergnaghi; A. Sarti; L. Mainardi; S. Cerutti

doi:10.1109/IEMBS.2006.260334

A Fuzzy-C-Means clustering algorithm for a volumetric analysis of paranasal sinus and nasal cavity cancers

K. Passera, P. Potepan, E. Setti, D. Vergnaghi, A. Sarti, L. Mainardi, S. Cerutti

Fondazione IRCCS Istituto Nazionale dei Tumori

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, a semi-automatic segmentation algorithm for volumetric analysis of paranasal sinus and nasal cavity cancers is presented and validated. The algorithm, based on a semi-supervised Fuzzy-C-means method, was applied to a Magnetic Resonance data sets (each of them composed by T1-weighted, Contrast Enhanced T1-weighted and T2-weighted images) for a total of 64 tumor-contained slices. Method performances are tested by both a numerical and a clinical validation. Results show that the proposed method has a higher accuracy in quantifying lesion area than a Region Growing algorithm and it can be applied in the evaluation of tumor response to therapy.

Original language	English
Title of host publication	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Pages	3078-3081
Number of pages	4
DOIs	https://doi.org/10.1109/IEMBS.2006.260334
Publication status	Published - 2006
Event	28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 - New York, NY, United States Duration: Aug 30 2006 → Sep 3 2006

Other

Other	28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Country/Territory	United States
City	New York, NY
Period	8/30/06 → 9/3/06

ASJC Scopus subject areas

Bioengineering

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10.1109/IEMBS.2006.260334

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Passera, K., Potepan, P., Setti, E., Vergnaghi, D., Sarti, A., Mainardi, L., & Cerutti, S. (2006). A Fuzzy-C-Means clustering algorithm for a volumetric analysis of paranasal sinus and nasal cavity cancers. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings (pp. 3078-3081). [4029304] https://doi.org/10.1109/IEMBS.2006.260334

A Fuzzy-C-Means clustering algorithm for a volumetric analysis of paranasal sinus and nasal cavity cancers. / Passera, K.; Potepan, P.; Setti, E.; Vergnaghi, D.; Sarti, A.; Mainardi, L.; Cerutti, S.

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 2006. p. 3078-3081 4029304.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Passera, K, Potepan, P, Setti, E, Vergnaghi, D, Sarti, A, Mainardi, L & Cerutti, S 2006, A Fuzzy-C-Means clustering algorithm for a volumetric analysis of paranasal sinus and nasal cavity cancers. in Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings., 4029304, pp. 3078-3081, 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06, New York, NY, United States, 8/30/06. https://doi.org/10.1109/IEMBS.2006.260334

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AB - In this paper, a semi-automatic segmentation algorithm for volumetric analysis of paranasal sinus and nasal cavity cancers is presented and validated. The algorithm, based on a semi-supervised Fuzzy-C-means method, was applied to a Magnetic Resonance data sets (each of them composed by T1-weighted, Contrast Enhanced T1-weighted and T2-weighted images) for a total of 64 tumor-contained slices. Method performances are tested by both a numerical and a clinical validation. Results show that the proposed method has a higher accuracy in quantifying lesion area than a Region Growing algorithm and it can be applied in the evaluation of tumor response to therapy.

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A Fuzzy-C-Means clustering algorithm for a volumetric analysis of paranasal sinus and nasal cavity cancers

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