Accéder directement au contenu Accéder directement à la navigation
Communication dans un congrès

Computer-Aided Diagnosis of Diagnostically Challenging Lesions in Breast MRI: A Comparison between a Radiomics and a Feature-Selective Approach

Sebastian Hoffmann 1 Marc Lobbes, 2 Ivo Houben, 2 Katja Pinker-Domenig, 3, 4 Georg Wengert, 4 Bernhard Burgeth 5 Uwe Meyer-Base, 6 Guillaume Lemaître 7 Anke Meyer-Baese 1, 2
1 Dept Computer Science, Florida State University
2 Dept Radiol. Nuclear Medicine, Maastricht University
3 Memorial Sloane Kettering Cancer Center [New York]
4 Medizinische Universität Wien = Medical University of Vienna
5 Universität des Saarlandes [Saarbrücken]
6 Dept Elect and Comp Engn, Florida State University
7 Le2i - Laboratoire Electronique, Informatique et Image [UMR6306]
Abstract : Diagnostically challenging lesions pose a challenge both for the radiological reading and also for current CAD systems. They are not well-defined in both morphology (geometric shape) and kinetics (temporal enhancement) and pose a problem to lesion detection and classification. Their strong phenotypic differences can be visualized by MRI. Radiomics represents a novel approach to achieve a detailed quantification of the tumour phenotypes by analyzing a large number of image descriptors. In this paper, we apply a quantitative radiomics approach based on shape, texture and kinetics tumor features and evaluate it in comparison to a reduced-order feature approach in a computer-aided diagnosis system applied to diagnostically challenging lesions.
Keywords : Diagnostically challenging lesions morphological and kinetic features classification computer-aided diagnosis radiomics breast magnetic resonance imaging Enhancement Moments Tool
Type de document :
Communication dans un congrès
Liste complète des métadonnées
https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01438462
Contributeur : Le2i - Université de Bourgogne <>
Soumis le : mardi 17 janvier 2017 - 17:17:51
Dernière modification le : samedi 22 mai 2021 - 03:41:25

Identifiants

Collections

UNIV-BOURGOGNE | CNRS | LE2I | UNIV-HESAM | ARTS-ET-METIERS-SCIENCES-ET-TECHNOLOGIES

Citation

Sebastian Hoffmann, Marc Lobbes,, Ivo Houben,, Katja Pinker-Domenig,, Georg Wengert,, et al.. Computer-Aided Diagnosis of Diagnostically Challenging Lesions in Breast MRI: A Comparison between a Radiomics and a Feature-Selective Approach. Conference on Sensing and Analysis Technologies for Biomedical and Cognitive Applications, Apr 2016, Baltimore, MD, United States. pp.UNSP 98710H, ⟨10.1117/12.2228994⟩. ⟨hal-01438462⟩

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

641