Magnetic resonance brain images algorithm to identify demyelinating and ischemic diseases

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.

MR Images, Brain Lesions, and Deep Learning

“…Hence, neuroimaging plays a fundamental role in understanding how the brain and the nervous system function [3] and discover how structural or functional anatomical alteration is correlated with different neurological disorders [4] and brain lesions. Currently, research on artificial intelligence (AI) and diverse techniques of imaging constitutes a crucial tool for studying the brain [5][6][7][8][9][10][11] and aids the physician to optimize the time-consuming tasks of detection and segmentation of brain anomalies [12] and also to better interpret brain images [13] and analyze complex brain imaging data [14].…”

“…There are three types of ischemic stroke according to the Bamford clinical classification system [24]: (1) partial anterior circulation syndrome (PACS), where the middle/anterior cerebral regions are affected; (2) lacunar anterior circulation syndrome (LACS), where the occlusion is present in vessels that provide blood to the deep-brain regions; and (3) total anterior circulation stroke (TACS), when middle/anterior cerebral regions are affected due to a massive brain stroke [24,25]. Ischemic stroke is a common cerebrovascular disease [1,26,27] and one of the principal causes of death and disability in low-and middle-income countries [1,4,6,7,[27][28][29]. In developed countries, brain ischemia is responsible for 75-80% of strokes, and 10-15% are attributed to a hemorrhagic brain stroke [4,25].…”

“…In the past few years, there has been considerable research in the field of machine learning (ML) and deep learning (DL) to create automatic or semiautomatic systems, algorithms, and methods that allow detection of lesions in the brain, such as tumors, MS, stroke, glioma, AD, etc. [4,6,[8][9][10]26,28,30,36,[39][40][41][42][43][44][45][46][47][48]. Different studies demonstrate that deep learning algorithms can be successfully used for medical image retrieval, segmentation, computer-aided diagnosis, disease detection, and classification [49][50][51].…”

MRI Images, Brain Lesions and Deep Learning

“…Biomedical images give fundamental information necessary for the diagnosis, prognosis, and treatment of different pathologies. Of all the various imaging modalities neuroimaging, is a crucial tool for studying the brain [3][4][5][6][7][8][9]. In terms of neuroimaging of both normal and pathologies there are different modalities namely, (1): Computed Tomography (CT), and Magnetic Resonance images (MRI) which are commonly used for the structural visualization; (2) the Positron emission tomography (PET) used principally for physiological analysis; and (3) single-photon emission tomography (SPECT) and functional MRI which are used for functional analysis of the brain [10].…”

Assessment of mesial temporal sclerosis through MRI processing

“…Different works manifest the fundamental role of the neuroimaging in the determination of neurological diseases and disorders and the support that offer to neuroradiologist in giving an accurate diagnosis, prognosis, and monitoring, due also the neuroimaging has been recognized as a powerful tool to analyze brain changes. [1][2][3][4][5][6][7][8][9] Inside of this field, there are different modalities: e.g. for to analyze of the structure of the brain the Computed Tomography (CT) and Magnetic Resonance images (MRI) are the most used; and for to do a physiological analysis was used the Positron emission tomography (PET), single-photon emission tomography (SPECT) and functional MRI for to do a brain analysis of images 10,11 .…”