Detection method of cerebral aneurysm based on curvature analysis from 3D medical images

H. Prasetya, T. Mengko, O. Santoso, H. Zakaria
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引用次数: 5

Abstract

Cerebral aneurysm is a weak spot in a blood vessel that usually enlarges. Nowadays, cerebral aneurysm detection method is still being done manually by visually observing 2D or 3D medical images (CTA). The main purpose of this paper is to design a method of cerebral aneurysm detection and classify different vascular geometry with color indicator. The method developed was based on curvature analysis of wall vasculatures model that were reconstructed from 3D CTA images. The curvature shape index defined as I=(K1+K2)/K1 where K1 and K2 are the main curvature of vascular model then used as the base of vascular coloring system. Results showed that the shape index is able to differentiate different parts of vasculature model and detect the present of an aneurysm.
基于三维医学图像曲率分析的脑动脉瘤检测方法
脑动脉瘤是血管中的一个薄弱点,通常会扩大。目前,脑动脉瘤的检测方法仍然是通过肉眼观察二维或三维医学图像(CTA)手工完成的。本文的主要目的是设计一种脑动脉瘤的检测方法,并利用颜色指示器对不同的血管几何形状进行分类。该方法是基于三维CTA图像重建的血管壁模型的曲率分析。曲率形状指数定义为I=(K1+K2)/K1,其中K1和K2是血管模型的主要曲率,然后作为血管着色系统的基础。结果表明,形状指数能够区分血管模型的不同部位,并能检测出动脉瘤的存在。
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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