Advanced Detection of Brain Disease using ML and DL Algorithm

V. J, R. R
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Abstract

In today’s scenario, several brain and neurological disorders are being discovered and the complexity of structure of brain varies with age. The early diagnosis of these diseases is of utmost importance. so, the segmentation process of Magnetic resonance imaging is done to obtain maximum accuracy. Precise segmentation of the magnetic resonance imaging image is required for the diagnosing the brain tumor using laptop-based clinical requirement. Using each of the segmentation strategies, which method is best for segmenting the tumor can be identified from each of the images. This work proposes an advanced machine learning and deep learning based predictive method to forecast malignant and benign tumor. This is an effective and simple model for the detection and classification of brain tumor.
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基于ML和DL算法的脑部疾病高级检测
在今天的情况下,一些大脑和神经系统疾病正在被发现,大脑结构的复杂性随着年龄的增长而变化。这些疾病的早期诊断是至关重要的。因此,对磁共振成像进行分割处理,以获得最大的精度。基于笔记本电脑的脑肿瘤诊断临床需要对磁共振成像图像进行精确分割。使用每种分割策略,可以从每个图像中识别出最适合分割肿瘤的方法。本文提出了一种基于机器学习和深度学习的恶性肿瘤和良性肿瘤预测方法。这是一种简便有效的脑肿瘤检测与分类模型。
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