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An improved active contour model for medical images segmentation.

机译:用于医学图像分割的改进的主动轮廓模型。

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摘要

Image Segmentation is an image processing technique which is used to subdivide an image into regions in which each one contains components having similar properties or characteristics. Its goal is to "simplify and/or change the representation of an image into something that is more meaningful and easier to analyze". This approach has many applications. One of its most important applications is the extraction of tumor areas from medical images as a first step in the therapy planning of cancer patients. This objective can be achieved by many image segmentation approaches. One of these successful techniques is the active contour (Snake); its idea is based on a flexible curve (or surface) which is dynamically adapted to required edges or objects in an image. In this work an improvement over a current active contour model is proposed. The new model was tested using real CT images and has given promising results.
机译:图像分割是一种图像处理技术,用于将图像细分为每个区域都包含具有相似属性或特性的组件。其目标是“将图像的表示简化和/或更改为更有意义且更易于分析的内容”。这种方法有许多应用。它最重要的应用之一是从医学图像中提取肿瘤区域,这是癌症患者治疗计划的第一步。该目的可以通过许多图像分割方法来实现。这些成功的技术之一是主动轮廓(Snake)。它的思想是基于可弯曲的曲线(或曲面),该曲线可动态适应图像中所需的边缘或对象。在这项工作中,提出了对当前主动轮廓模型的改进。使用真实的CT图像测试了新模型,并给出了可喜的结果。

著录项

  • 作者单位

    King Fahd University of Petroleum and Minerals (Saudi Arabia).;

  • 授予单位 King Fahd University of Petroleum and Minerals (Saudi Arabia).;
  • 学科 Engineering System Science.;Health Sciences Radiology.;Engineering Biomedical.
  • 学位 M.S.
  • 年度 2010
  • 页码 120 p.
  • 总页数 120
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:37:34

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