MRI Texture-Based Classification of Dystrophic Muscles. A Search for the Most Discriminative Tissue Descriptors
| Autor: | Marek Kretowski, Jacques D. de Certaines, Dorota Duda, Noura Azzabou |
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| Přispěvatelé: | Białystok University of Technology, Institute of Myology, Nuclear Magnetic Resonance Laboratory, Institut d'Imagerie BioMédicale (I2BM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Service MIRCEN (MIRCEN), Institut de Biologie François JACOB (JACOB), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Khalid Saeed, Władysław Homenda, TC 8, Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie François JACOB (JACOB), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Boosting (machine learning) Computer science [SHS.INFO]Humanities and Social Sciences/Library and information sciences Feature selection Texture (music) 03 medical and health sciences Golden Retriever Muscular Dystrophy (GRMD) Duchenne Muscular Dystrophy (DMD) 0302 clinical medicine Discriminative model medicine [INFO]Computer Science [cs] MRI T2 medicine.diagnostic_test Artificial neural network business.industry Dystrophy Magnetic resonance imaging Pattern recognition Classification Support vector machine 030104 developmental biology Texture analysis Artificial intelligence business 030217 neurology & neurosurgery |
| Zdroj: | Lecture Notes in Computer Science 15th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM) 15th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Sep 2016, Vilnius, Lithuania. pp.116-128, ⟨10.1007/978-3-319-45378-1_11⟩ Computer Information Systems and Industrial Management ISBN: 9783319453774 CISIM |
| Popis: | Part 3: Images, Visualization, Classification; International audience; The study assesses the usefulness of various texture-based tissue descriptors in the classification of canine hindlimb muscles. Experiments are performed on T2-weighted Magnetic Resonance Images (MRI) acquired from healthy and Golden Retriever Muscular Dystrophy (GRMD) dogs over a period of 14 months. Three phases of canine growth and/or dystrophy progression are considered. In total, 39 features provided by 8 texture analysis methods are tested. Features are ranked according to their frequency of selection in a modified Monte Carlo procedure. The top-ranked features are used in differentiation (i) between GRMD and healthy dogs at each phase of canine growth, and (ii) between three phases of dystrophy progression in GRMD dogs. Three classifiers are applied: Adaptive Boosting, Neural Networks, and Support Vector Machines. Small sets of selected features (up to 10) are found to ensure highly satisfactory classification accuracies. |
| Databáze: | OpenAIRE |
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