Application of Fuzzy Image Concept to Medical Images Matching

被引：5
|
作者：
Zarychta, Piotr [1 ]
机构：
[1] Silesian Tech Univ, Fac Biomed Engn, Roosevlta 40, Zabrze, Poland
来源：
INFORMATION TECHNOLOGY IN BIOMEDICINE (ITIB 2018) | 2019年 / 762卷
关键词：
Entropy measure of fuzziness; Similarity measures; Medical image matching; Knee joint; Cruciate ligament; REGISTRATION; SEGMENTATION; EXTRACTION; ANTERIOR;
D O I：
10.1007/978-3-319-91211-0_3
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The main aim of this research is presenting an automated image matching methodology being used in the field of medicine for inter- and intraobjectional image matching. This paper shows a different approach avoiding the standard procedures associated with performing four main steps of the registration process: feature detection, feature matching, mapping function design and image transformation with resampling, and replacing them with the fuzzy image concept combined with the use of similarity measures. This methodology has been implemented in MATLAB and tested on clinical T1- and T2-weighted magnetic resonance imaging (MRI) slices of the knee joint in coronal and sagittal plane.
引用
收藏
页码：27 / 38
页数：12
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