脑积水和脑萎缩分类的新特征

Manit Chansuparp, Annupan Rodtook, Suwanna Rasmequan, K. Chinnasarn
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引用次数: 1

摘要

目前脑积水(HC)的影像学诊断仍然是该地区大多数研究人员关注的主要问题。这是因为脑积水(HC)和脑萎缩(CA)的临床症状和影像学表现具有相似的特征。本文提出利用脑沟比(SR)和额枕角角(FOHA)两个新特征,结合Evans比、额枕角比和脑室角等典型特征对HC和CA进行分类。实验结果表明,HC和CA的脑沟比存在差异。因此,这种比率可以在很大程度上帮助区分HC和CA。与该领域最近的研究相比,这两个新特征的使用是一个有吸引力的改进。这些研究主要集中在心室,这使得从MRI图像中区分HC和CA更加困难。从HC分类中,我们的方法的性能提高了59%的真阳性率,36.8%的假阳性率和66.1%的F-measure。在分类上分别提高36.8%、59%和36.6%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel features for classification of hydrocephalus and cerebral atrophy
Present radiologic diagnosis of hydrocephalus (HC) are still the main concern for most researchers in the area. This is due to the fact that clinical symptoms and radiographic image of both Hydrocephalus (HC) and Cerebral Atrophy (CA) have similar characters. In this paper, we propose to use two new features: Sulci-Ratio (SR) and Frontal and Occipital Horn Angle (FOHA) together with typical features: Evans Ratio, Frontal and Occipital Horn Ratio and Ventricular Angle to classify between HC and CA. The experimental results show that Sulci-Ratios of HC and CA are difference. So this kind of ratio can help a lot in differentiate between HC and CA. The use of these two new features makes an attractive improvement as compare to most recent researches in the field. Those researches are mainly focus on the Ventricular which makes it more difficult to distinguish between HC and CA from MRI images. The performance of our methods is improved by 59% of true positive rate, 36.8% of false positive rate and 66.1% of F-measure from the classification of HC. In classification of CA is improved by 36.8%, 59% and 36.6% respectively.
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