Computer-Aided Diagnosis of Diagnostically Challenging Lesions in Breast MRI: A Comparison between a Radiomics and a Feature-Selective Approach
| Autor: | Marc B. I. Lobbes, Uwe Meyer-Bäse, Katja Pinker-Domenig, Anke Meyer-Baese, I. P. L. Houben, Guillaume Lemaitre, Bernhard Burgeth, Sebastian Hoffmann, Georg Wengert |
|---|---|
| Přispěvatelé: | Dept Computer Science, Florida State University, Florida State University [Tallahassee] (FSU), Dept Radiol. Nuclear Medicine, Maastricht University, Maastricht University [Maastricht], Memorial Sloane Kettering Cancer Center [New York], Medizinische Universität Wien = Medical University of Vienna, Universität des Saarlandes [Saarbrücken], Dept Elect and Comp Engn, Florida State University, Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Sponsor(s):SPIE, Dai, L, Zheng, Y, Chu, H, MeyerBase, AD, Florida State University [Tallahassee] ( FSU ), Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Moments
Visual descriptors ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Diagnostically challenging lesions 030218 nuclear medicine & medical imaging 03 medical and health sciences [SPI]Engineering Sciences [physics] 0302 clinical medicine Radiomics 0202 electrical engineering electronic engineering information engineering [ SPI ] Engineering Sciences [physics] Medicine Breast MRI Computer vision breast magnetic resonance imaging morphological and kinetic features ComputingMethodologies_COMPUTERGRAPHICS [PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics] [ PHYS.PHYS.PHYS-OPTICS ] Physics [physics]/Physics [physics]/Optics [physics.optics] Lesion detection medicine.diagnostic_test business.industry Enhancement Magnetic resonance imaging Cad system ComputingMethodologies_PATTERNRECOGNITION classification Computer-aided diagnosis Feature (computer vision) radiomics Tool 020201 artificial intelligence & image processing computer-aided diagnosis Artificial intelligence business |
| Zdroj: | Sensing and Analysis Technologies for Biomedical and Cognitive Applications 2016 Conference on Sensing and Analysis Technologies for Biomedical and Cognitive Applications Conference on Sensing and Analysis Technologies for Biomedical and Cognitive Applications, Apr 2016, Baltimore, MD, United States. pp.UNSP 98710H, ⟨10.1117/12.2228994⟩ Dai, L; Zheng, Y ; Chu, H; MeyerBase, AD. Conference on Sensing and Analysis Technologies for Biomedical and Cognitive Applications, Apr 2016, Baltimore, MD, United States. SPIE-INT SOC OPTICAL ENGINEERING, 1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98227-0010 USA, Sensing and Analysis Technologies for Biomedical and Cognitive Applications 2016, 9871, pp.UNSP 98710H, 2016, Proceedings of SPIE. 〈http://spie.org/Publications/Proceedings/Paper/10.1117/12.2228994〉. 〈10.1117/12.2228994〉 |
| DOI: | 10.1117/12.2228994⟩ |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|