先进脑肿瘤检测系统

Monica S. Kumar, Swathi K. Bhat, V. R. Thakare
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引用次数: 0

摘要

脑肿瘤的分割与检测是目前医学领域的关键问题之一。肿瘤是一种癌症类型,在原发性和继发性肿瘤的情况下,可以在身体的任何部位看到。脑肿瘤的不同类型有胶质瘤、良性、恶性、脑膜瘤。这项研究有助于在二维MRI图像的帮助下检索大脑中的肿瘤区域。该系统采用MATLAB编程平台进行预测,并采用canny边缘、Otsu二值、模糊c-均值(FCM)、k-均值聚类等不同的方法对肿瘤进行分析,利用像素技术改进边界。该系统采用卷积神经网络(CNN)、神经网络和自然语言处理技术,基于预处理和后处理特征对脑肿瘤进行检测。此外,作者还指出,在早期阶段,受影响的肿瘤是保护寿命的最重要特征。最后,它以邮件格式向医生或患者确认结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advanced Brain Tumor Detection System
Brain tumor segmentation and detection is one of the most critical parts in the field of medical regions. Tumor is a cancer type that can be visible in any part of the body in case of primary and secondary tumor. The different type of brain tumor is glioma, benign, malignant, meningioma. This research helps in retrieving the tumor region in the brain with the help of 2D MRI images. The system predicts using MATLAB which is a programming platform and analyze the tumor from different method like canny edge, Otsu's binary, fuzzy c-means (FCM), and k-means clustering to improve the borders using the pixel technique. Using convolution neural network (CNN), neural network, and natural language processing, the system detects brain tumor based on the pre-processing and post-processing feature. Moreover, the authors figure out which tumor affected is the most important feature to protect the lifespan in the initial stages. Finally, it acknowledges the result in the mail format to the doctor or patient.
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