Object localization in medical images

Radek Benes, Martin Hasmanda, K. Říha
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引用次数: 14

Abstract

This paper is focused on localization of objects in medical images. A novel improvement of an existing method for localization of artery in longitudinal ultrasound B-mode scan is proposed in the paper. The localization is based on a classification of pixels according to image information in their neighborhood. To suppress misclassified points, a novel RANSAC based method is proposed. This method is able to find the most appropriate mathematical model of depicted common carotid artery (CCA) on the basis of previous classification. The proposed RANSAC based method with its mathematical footing is described in detail and the results of method within the algorithm for localization of artery are enclosed. By using the proposed RANSAC based method the localization method becomes very robust.
医学图像中的目标定位
本文主要研究医学图像中物体的定位问题。本文提出了一种改进现有的纵向超声b型扫描动脉定位方法的方法。定位是基于像素的分类,根据图像信息在他们的邻居。为了抑制误分类点,提出了一种基于RANSAC的新方法。该方法能够在前人分类的基础上找到最合适的描述颈总动脉的数学模型。文中详细描述了基于RANSAC的动脉定位方法及其数学基础,并给出了算法中的结果。采用基于RANSAC的定位方法,使定位方法具有较强的鲁棒性。
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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