Evaluation of Classifiers for the Identification of Multiple Sclerosis Lesions in Neural MRI Scans with Attributes Extracted from Pre-trained Neural Networks
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-49404-8_14
Reference21 articles.
1. Walton, C., King, R., Rechtman, L., et al.: Rising prevalence of multiple sclerosis worldwide: insights from the Atlas of MS. Mult. Scler. J. 26(14), 1816–1821 (2020)
2. Roy, S., Butman, J.A., Reich, D.S., et al.: Multiple sclerosis lesion segmentation from brain MRI via fully convolutional neural networks. arXiv preprint arXiv:1803.09172 (2018)
3. Dobson, R., Giovannoni, G.: Multiple sclerosis–a review. Eur. J. Neurol. 26(1), 27–40 (2019)
4. Louapre, C.: Conventional and advanced MRI in multiple sclerosis. Revue Neurologique 174(6), 391–397 (2018)
5. de Arruda, A.L.C., Vital, D.A., Kitamura, F.C., et al.: Multiple sclerosis segmentation method in magnetic resonance imaging using fuzzy connectedness, binarization, mathematical morphology, and 3D reconstruction. Res. Biomed. Eng. 36(3), 291–301 (2020)
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