首页> 外文会议>International conference on computational collective intelligence >Articular Cartilage Defect Detection Based on Image Segmentation with Colour Mapping
【24h】

Articular Cartilage Defect Detection Based on Image Segmentation with Colour Mapping

机译:基于颜色映射的图像分割的关节软骨缺损检测

获取原文

摘要

This article addresses a possible approach for a higher quality diagnosis and detection of the pathological defects of articular cartilage. The defects of articular cartilage are one of the most common pathologies of articular cartilage that a physician encounters. In clinical practice, doctors can only estimate visually whether or not there is a pathological defect with the use of magnetic resonance images. Our proposed methodology is able to accurately and precisely localize ruptures of cartilaginous tissue and thus greatly contribute to improving a final diagnosis. When analysing MRI data, we work only with grey-levels, which is rather complicated for producing a quality diagnosis. Our proposed algorithm, based on fuzzy logic, brings together various shades of grey. Each set is assigned a colour that corresponds to the density of the tissue. With this procedure, it is possible to create a contrast map of individual tissue structures and very clearly identify where cartilaginous tissues have been interrupted. The suggested methodology has been tested using real data from magnetic resonance images of 60 patients from Podlesf Hospital in Tfinec and currently this method is being put into clinical practice.
机译:本文介绍了一种可能的方法,可以对关节软骨的病理学缺陷进行更高质量的诊断和检测。关节软骨缺损是医师遇到的最常见的关节软骨病理之一。在临床实践中,医生只能使用磁共振图像通过视觉估计是否存在病理缺陷。我们提出的方法能够准确,准确地定位软骨组织的破裂,从而极大地有助于改善最终诊断。在分析MRI数据时,我们仅使用灰度级,这对于产生质量诊断而言相当复杂。我们提出的算法基于模糊逻辑,汇集了各种灰色阴影。每组分配有一种颜色,该颜色与组织的密度相对应。通过此程序,可以创建单个组织结构的对比图,并非常清楚地识别出软骨组织已被中断的位置。使用来自Tfinec Podlesf医院的60例患者的磁共振图像的真实数据对建议的方法进行了测试,目前该方法正在临床实践中。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号