A fuzzy multilayer perceptron network based detection and classification of lobar intra-cerebral hemorrhage from Computed Tomography images of brain

A. Datta, Ashis Datta, Biswajit Biswas
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引用次数: 5

Abstract

Medical imaging techniques and analysis tools like Computed Tomography (CT) enable the doctors and radiologists to identify as well as diagnose various disorders in internal structures. In this paper, fuzzy multilayer perceptron network based algorithm used for segmentation and region classification and region severance algorithm is used for detection and location of Intra-cerebral hemorrhage. According to location different types of lobar Intra-cerebral hemorrhages are classified. Experimental visualization results are presented which were computed on real intra-cerebral hemorrhage patient brain data. The objective of this paper is to propose a method to assist the radiologists in identifying the different type of lobar Intracerebral hemorrhage and to arrive at a decision faster and accurate.
基于模糊多层感知器网络的脑ct图像中脑叶性脑出血的检测与分类
医学成像技术和计算机断层扫描(CT)等分析工具使医生和放射科医生能够识别和诊断内部结构中的各种疾病。本文采用基于模糊多层感知器网络的分割和区域分类算法和区域分离算法对脑出血进行检测和定位。根据部位不同,可将不同类型的大叶性脑出血进行分类。根据脑出血患者的真实脑数据,给出了可视化的实验结果。本文的目的是提出一种方法,以协助放射科医师识别不同类型的脑叶性脑出血,并更快、准确地作出决定。
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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