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 |
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Title of host publication | Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings |
Pages | 3078-3081 |
Number of pages | 4 |
DOIs | |
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 |
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Country | United States |
City | New York, NY |
Period | 8/30/06 → 9/3/06 |
ASJC Scopus subject areas
- Bioengineering