Abstract
Duchenne muscular dystrophy (DMD) is a fatal Xlinked muscle disorder caused by mutations in the dystrophin gene with a consequence of progressive degeneration of skeletal and cardiac muscle. Golden retriever muscular dystrophy (GRMD) is a spontaneous X-linked canine model of DMD with similar effects. Due to high soft-tissue contrast images, MRI is preferred as a non-invasive method to extract information corresponding to biological characteristics. We propose and evaluate non-invasive MRI-based imaging biomarkers to assess the severity of golden retriever muscular dystrophy (GRMD) using 3T and 4.7T MRI data of nine animals. These imaging biomarkers use first order statistics and texture (assessed by wavelets) in quantitative MRI (qMRI). In a leave-one-sampleout cross-validation framework, we use SVM to differentiate between young and old GRMD animals. The preliminary results show good differentiation between young and old animals for different qMRI sequences and based on a different selection of features.
Original language | English |
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Title of host publication | 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 |
Publisher | IEEE |
Pages | 648-651 |
Number of pages | 4 |
ISBN (Electronic) | 9781538636466 |
DOIs | |
Publication status | Published - 29 Oct 2018 |
Externally published | Yes |
Event | 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 - Hawaii Convention Center, Honolulu, United States Duration: 17 Jul 2018 → 21 Jul 2018 Conference number: 40 https://embc.embs.org/2018/ |
Conference
Conference | 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 |
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Abbreviated title | EMBC 2018 |
Country/Territory | United States |
City | Honolulu |
Period | 17/07/18 → 21/07/18 |
Internet address |
Keywords
- GRMD
- image classification
- image registration
- image segmentation
- MRI biomarkers