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

机译:基于模糊多层的脑部巨大脑内出血的基于模糊多层的植物网络检测与分类

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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.
机译:诸如计算机断层扫描(CT)等医学成像技术和分析工具使医生和放射科医生能够识别以及诊断内部结构中的各种障碍。本文采用了用于分割和区域分类和区域转断算法的模糊多层Perceptron网络算法用于脑内出血的检测和位置。根据定位不同类型的洛巴寡不振内出血分类。提出了实验性可视化结果,其在真正的脑内出血患者脑数据上计算。本文的目的是提出一种方法来帮助放射科医师鉴定不同类型的鳞叶鳞状脑内出血,并以更快和准确的决定来达到决策。

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