Classification of calf muscle MR images by texture analysis

被引:0
|
作者
A. Škoch
D. Jirák
P. Vyhnanovská
M. Dezortová
P. Fendrych
E. Rolencová
M. Hájek
机构
[1] Institute for Clinical and Experimental Medicine,MR spectroscopy, Department of Diagnostic and Interventional Radiology
[2] Charles University,Centre for Cell Therapy and Tissue Repair
关键词
MR imaging; Statistical analysis; Texture analysis; Principal component analysis; Automatic classification; Calf muscle;
D O I
暂无
中图分类号
学科分类号
摘要
Aim: To evaluate a method of texture analysis (TA) for the description of magnetic resonance (MR) images of healthy and diseased calf muscles and to compare this method with standard radiological evaluation. Methods: A total of 93 subjects (20 controls, seven healthy children of hypertonic parents, five diabetic patients and 61 subjects with muscle malfunction of various origin) underwent MR imaging of the calf muscle and texture analysis of images was performed. The results of TA were analysed by t-statistics and principal component analysis. Images of subjects were divided into four groups according to the assessment of three radiologists and this categorization of subjects was compared with the results from TA. Results: We extracted seven features (from a total number of 282) which were successfully used for the description of the texture of T1w MR images of calf muscles. The results of classification by TA are in 80% agreement with the categorization made by the radiologists. In some cases, TA is able to describe changes not apparent by visual inspection. Conclusion: The TA of MR images of calf muscles can be used for the objective description of changes in muscles and could help radiologists to distinguish between healthy and diseased tissue.
引用
收藏
页码:259 / 267
页数:8
相关论文
共 50 条
  • [1] Classification of calf muscle MR images by texture analysis
    Skoch, A
    Jirák, D
    Vyhnanovská, P
    Dezortová, M
    Fendrych, P
    Rolencová, E
    Hájek, M
    MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE, 2004, 16 (06) : 259 - 267
  • [2] Classification of cirrhotic liver on MR images using texture analysis
    Lee, G. N.
    Zhang, X.
    Kanematsu, M.
    Zhou, X.
    Hara, T.
    Kato, H.
    Kondo, H.
    Fujita, H.
    Hoshi, H.
    INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2006, 1 : 379 - 381
  • [3] Multi-sequence texture analysis in classification of in vivo MR images of the prostate
    Duda, Dorota
    Kretowski, Marek
    Mathieu, Romain
    de Crevoisier, Renaud
    Bezy-Wendling, Johanne
    BIOCYBERNETICS AND BIOMEDICAL ENGINEERING, 2016, 36 (04) : 537 - 552
  • [4] TEXTURE ANALYSIS OF BRAIN MR IMAGES
    Vanamala, H. R.
    Nandur, Deeksha
    Ashutosh, C.
    Glavan, F.
    Ganesh, M. H.
    2018 SECOND INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRONICS, COMPUTERS AND COMMUNICATIONS (ICAECC), 2018,
  • [5] Texture Classification Study of MR Images for Hepatocellular Carcinoma
    Qiu J.-J.
    Wu Y.
    Hui B.
    Liu Y.-B.
    Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China, 2019, 48 (04): : 619 - 626
  • [6] Morphological and Texture Based Classification of Dementia from MR Images
    Bhalerao, Gaurav V.
    Hrabuska, Radek
    Sampathila, Niranjana
    JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2017, 7 (02) : 293 - 304
  • [7] Texture Analysis of Brain MR Images for Age Detection
    Al-Hazzouri, Freddy
    Bazzi, Farah
    Diab, Ahmad
    2021 SIXTH INTERNATIONAL CONFERENCE ON ADVANCES IN BIOMEDICAL ENGINEERING (ICABME), 2021, : 99 - 102
  • [8] Texture Analysis for Classification of Thyroid Ultrasound Images
    Nugroho, Hanung Adi
    Rahmawaty, Made
    Triyani, Yuli
    Ardiyanto, Igi
    2016 INTERNATIONAL ELECTRONICS SYMPOSIUM (IES), 2016, : 476 - 480
  • [9] Texture analysis and classification of ultrasound liver images
    Gao, Shuang
    Peng, Yuhua
    Guo, Huizhi
    Liu, Weifeng
    Gao, Tianxin
    Xu, Yuanqing
    Tang, Xiaoying
    BIO-MEDICAL MATERIALS AND ENGINEERING, 2014, 24 (01) : 1209 - 1216
  • [10] Texture features’ based classification of MR images of normal and herniated intervertebral discs
    Bazila Hashia
    Ajaz Hussain Mir
    Multimedia Tools and Applications, 2020, 79 : 15171 - 15190