A systematic approach for brain abnormality identification from biomedical images

Rupal Snehkunj, Ashish Jani
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引用次数: 1

Abstract

Since many years the brain disease has affected many lives. The mortality rate has not reduced despite of consistent efforts have been made to overcome the problems of brain abnormality. Brain abnormalities (Infections, trauma, seizures, and tumors, hemorrhage (stroke) and others) identification from medical images is challenging and time consuming because of manual or semi-automated approaches. The field needs automatic detection systems. The framework proposed in this paper will fulfill the requirement by classifying certain abnormalities which are malignant and benign in nature. Also, the system will assist the radiologist in accurate prediction of the progression of brain abnormalities which will help the society to save many lives.
基于生物医学图像的脑异常识别系统方法
多年来,这种脑部疾病影响了许多人的生活。尽管一直在努力克服大脑异常的问题,但死亡率并没有降低。由于采用手动或半自动方法,从医学图像中识别大脑异常(感染、创伤、癫痫、肿瘤、出血(中风)等)具有挑战性且耗时。现场需要自动检测系统。本文提出的框架将通过对某些本质上是恶性和良性的异常进行分类来满足这一要求。此外,该系统将帮助放射科医生准确预测大脑异常的进展,这将有助于社会挽救许多生命。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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