Computer-Aided Diagnosis of Diagnostically Challenging Lesions in Breast MRI: A Comparison between a Radiomics and a Feature-Selective Approach
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | Computer-Aided Diagnosis of Diagnostically Challenging Lesions in Breast MRI: A Comparison between a Radiomics and a Feature-Selective Approach |
| Type de publication | Conference Paper |
| Year of Publication | 2016 |
| Auteurs | Hoffmann S, Lobbes M, Houben I, Pinker-Domenig K, Wengert G, Burgeth B, Meyer-Base U, Lemaitre G, Meyer-Baese A |
| Editor | Dai L, Zheng Y, Chu H, MeyerBase AD |
| Conference Name | SENSING AND ANALYSIS TECHNOLOGIES FOR BIOMEDICAL AND COGNITIVE APPLICATIONS 2016 |
| Publisher | SPIE |
| Conference Location | 1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98227-0010 USA |
| ISBN Number | 978-1-5106-0112-3 |
| Mots-clés | breast magnetic resonance imaging, Classification, Computer-Aided Diagnosis, Diagnostically challenging lesions, morphological and kinetic features, radiomics |
| Résumé | 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. |
| DOI | 10.1117/12.2228994 |