Magnetic resonance brain images algorithm to identify demyelinating and ischemic diseases

D. Castillo; René Samaniego; Y. Jiménez; L. Cuenca; O. Vivanco; M. J. Rodríguez-Álvarez

doi:10.1117/12.2322048

17 September 2018 Magnetic resonance brain images algorithm to identify demyelinating and ischemic diseases

D. Castillo, René Samaniego, Y. Jiménez, L. Cuenca, O. Vivanco, M. J. Rodríguez-Álvarez

Proceedings Volume 10752, Applications of Digital Image Processing XLI; 107521W (2018) https://doi.org/10.1117/12.2322048
Event: SPIE Optical Engineering + Applications, 2018, San Diego, California, United States

Abstract

Brain demyelination lesions occur due to damage of the myelin layer of nerve fibers, this deterioration is the cause of pathologies such as multiple sclerosis, leukodystrophy, encephalomyelitis. Brain ischemia is the interruption of the blood supply to the brain, and the flow of oxygen and nutrients needed to maintain the correct functioning of brain cells. This project presents the results of an algorithm processing images with the the main objective of identify and differentiate between demyelination and ischemic brain diseases through the automatic detection, classification and identification of their features found in the magnetic resonance images. The sequences of images used were T1, T2, and FLAIR and with a dataset of 300 patients with and without these or other pathologies, respectively. The algorithm in this stage uses Discrete Wavelet Transform (DWT), principal component analysis (PCA) and a kernel support vector machine (SVM). The algorithm developed indicates a 75% of accuracy, for that reason, with an effective validation could be applied for the fast diagnosis and contribute to an effective treatment of these brain diseases especially in the rural places.

Conference Presentation

Citation Download Citation

D. Castillo, René Samaniego, Y. Jiménez, L. Cuenca, O. Vivanco, and M. J. Rodríguez-Álvarez "Magnetic resonance brain images algorithm to identify demyelinating and ischemic diseases", Proc. SPIE 10752, Applications of Digital Image Processing XLI, 107521W (17 September 2018); https://doi.org/10.1117/12.2322048

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