混合水平集在胎儿轮廓提取中的作用

Rachana Jaiswal, S. Satarkar
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引用次数: 0

摘要

在医学图像的分析和特征提取中,图像处理技术可以用于更快、更准确的诊断。本文对现有的水平集算法进行了改进,并将其用于提取图像中的胎儿轮廓。传统的方法是人工从超声图像中提取胎儿参数。由于传统的胎儿生物特征测量方法存在一致性和准确性不高的问题,自动化技术是实现胎儿生物特征测量的迫切需要。该方法利用全局和局部信息从超声图像中提取胎儿轮廓。本研究的主要目标是开发一种新的方法来辅助分析和特征提取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Role of Hybrid Level Set in Fetal Contour Extraction
Image processing technologies may be employed for quicker and accurate diagnosis in analysis and feature extraction of medical images. Here, existing level set algorithm is modified and it is employed for extracting contour of fetus in an image. In traditional approach, fetal parameters are extracted manually from ultrasound images. An automatic technique is highly desirable to obtain fetal biometric measurements due to some problems in traditional approach such as lack of consistency and accuracy. The proposed approach utilizes global & local region information for fetal contour extraction from ultrasonic images. The main goal of this research is to develop a new methodology to aid the analysis and feature extraction.
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