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SPEQTACLE: a Hilbertian norm generalization of the Fuzzy C-Means algorithm for tumor delineation in PET/CT images

Abstract : Accurate and robust tumor delineation in PET/CT images is crucial in oncology and radiotherapy and is still challenging for tumors with complex shapes, low signal-to-noise ratio and high uptake heterogeneity. We have developed a method called SPEQTACLE, based on a generalization of the Fuzzy C-Means (FCM) algorithm using a Hilbertian norm, estimated for each modality through an automatic scheme on each image. Robustness of the algorithm was assessed on multiple phantom acquisitions. Accuracy was evaluated on simulated and clinical images. On PET images, SPEQTACLE demonstrated high performance with significant improvement over the state-of-the-art for the most complex cases. For PET/CT cases, SPEQTACLE provided results in high agreement with manual delineations, outperforming other FCM implementation.
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Conference papers
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https://www.hal.inserm.fr/inserm-01155381
Contributor : Frédérique Frouin <>
Submitted on : Tuesday, May 26, 2015 - 3:25:21 PM
Last modification on : Wednesday, June 24, 2020 - 4:18:10 PM
Long-term archiving on: : Monday, April 24, 2017 - 3:30:00 PM

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  • HAL Id : inserm-01155381, version 1

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Jérôme Lapuyage-Lahorgue, Dimitris Visvikis, Mathieu Hatt. SPEQTACLE: a Hilbertian norm generalization of the Fuzzy C-Means algorithm for tumor delineation in PET/CT images. Journées RITS 2015, Mar 2015, Dourdan, France. pp 186-187. ⟨inserm-01155381⟩

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