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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Pages3078-3081
Number of pages4
DOIs
Publication statusPublished - 2006
Event28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 - New York, NY, United States
Duration: Aug 30 2006Sep 3 2006

Other

Other28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
CountryUnited States
CityNew York, NY
Period8/30/069/3/06

ASJC Scopus subject areas

  • Bioengineering

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