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一种基于主动轮廓模型的超声图像轮廓提取方法。

A contour extraction method using active contour model on ultrasonic images.

作者信息

Oshiro Masakuni, Nishimura Toshihiro

机构信息

Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsu-ku, Kitakyushu, Japan.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:825-8. doi: 10.1109/IEMBS.2007.4352417.

Abstract

At excision operations of a breast tumor, a navigation to display three-dimensional models during the operations is demanded to grasp a position and a size of the tumor, and to decide an area of the excision. Speckle noises which are characteristic of an ultrasonic image are caused by interference of sound waves. The noises cause a low resolution of a region of interest (ROI), and those are obstacle of constructing recognizable three-dimensional image. To reconstruct a three-dimensional model from two-dimensional ultrasonic tomograms, a speckle reduction and a contour extraction of the ROI are demanded. The purpose of this study is a contour extraction of a ROI on ultrasonic images. An active contour model using a gradient vector flow was employed. The contour of a lesion area of the ultrasonic images which speckle are reduced was extracted.

摘要

在乳腺肿瘤切除手术中,需要一种在手术过程中显示三维模型的导航系统,以掌握肿瘤的位置和大小,并确定切除区域。超声图像特有的斑点噪声是由声波干扰引起的。这些噪声导致感兴趣区域(ROI)的分辨率较低,并且是构建可识别的三维图像的障碍。为了从二维超声断层图像重建三维模型,需要进行斑点减少和ROI的轮廓提取。本研究的目的是对超声图像上的ROI进行轮廓提取。采用了基于梯度向量流的主动轮廓模型。提取了减少斑点后的超声图像病变区域的轮廓。

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