MRI Texture Analysis for Differentiation Between Healthy and Golden Retriever Muscular Dystrophy Dogs at Different Phases of Disease Evolution

Abstract : In this study, a texture analysis is applied to T2-weighted Magnetic Resonance Images (MRI) of canine pelvic limbs in order to differentiate between Golden Retriever Muscular Dystrophy (GRMD) dogs and healthy ones. The differentiation is performed at three phases of canine growth and/or disease development: 2-4 months (the first phase), 5-6 months (the second phase), and 7 months and more (the third phase). Eight feature extraction methods (statistical, model-based, and filter-based) and five classifiers are tested. Four types of muscles are analyzed: the Extensor Digitorum Longus (EDL), the Gastrocnemius Lateralis (GasLat), the Gastrocnemius Medialis (GasMed) and the Tibial Cranialis (TC). The experiments were performed on five healthy and five GRMDdogs. Each of themuscles was considered separately. The best classification results were 95.81% (the EDL muscle), 97.19% (GasLat), and 91.37% (EDL) correctly recognized cases, for the first, second and third phase, respectively. These results were obtained with an SVM classifier.
Complete list of metadatas

https://hal.inria.fr/hal-01444470
Contributor : Hal Ifip <>
Submitted on : Tuesday, January 24, 2017 - 10:40:36 AM
Last modification on : Wednesday, March 20, 2019 - 3:06:03 PM
Long-term archiving on : Tuesday, April 25, 2017 - 7:23:02 PM

File

978-3-319-24369-6_21_Chapter.p...
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Dorota Duda, Marek Kretowski, Noura Azzabou, Jacques Certaines. MRI Texture Analysis for Differentiation Between Healthy and Golden Retriever Muscular Dystrophy Dogs at Different Phases of Disease Evolution. 14th Computer Information Systems and Industrial Management (CISIM), Sep 2015, Warsaw, Poland. pp.255-266, ⟨10.1007/978-3-319-24369-6_21⟩. ⟨hal-01444470⟩

Share

Metrics

Record views

311

Files downloads

226