DocumentCode
3508655
Title
Texture Analysis of MRI in Patients with Multiple Sclerosis Based on the Gray-Level Difference Statistics
Author
Liu, WeiFang ; Zhou, Xiaoxia ; Jiang, Guilian ; Tong, Longzheng
Author_Institution
Inst. of Biomed. Eng., Capital Med. Univ., Beijing
Volume
3
fYear
2009
fDate
7-8 March 2009
Firstpage
771
Lastpage
774
Abstract
Objective: To investigate the differences of texture features among macroscopic lesion white matter (LWM), normal appearing white matter (NAWM) in magnetic resonance images (MRI) from patients with multiple sclerosis (MS) and normal white matter (NWM) from normal controls by gray-level difference statistics, and to detect the hidden abnormality of NAWM. Methods: T2-weighted MRI of 26 MS patients and 26 healthy subjects were selected, and 26 regions of interests (ROI) were chosen from MS patient MRI and healthy subject MRI for LWM, NAWM and NWM respectively. All of the ROI were analyzed by gray-level difference statistics, and contrast, angular second moment, mean and entropy those four texture features were extracted. Finally statistic significance was tested among three groups. Results: In LWM, NAWM and NWM groups, the increasing tendency was shown for angular second moment (0.1108, 0.2173 and 0.2649) , while decreasing tendency for contrast (41.5534, 9.4723 and 4.7341) mean(0.0184, 0.0086 and 0.0064) and entropy (1.0745, 0.7715 and 0.6648). Except contrast that the difference was not significant (P=0.26) between NAWM and NWM , the rests had significant differences (P<0.05) between LWM and NAWM (or NWM) or NAWM and NWM. Conclusion: Texture analysis can possible reveal the microscopic abnormality in patients with MS,and will be beneficial to the research of early diagnosis and treatment estimate of MS.
Keywords
biomedical MRI; diseases; feature extraction; image texture; medical image processing; statistical analysis; MRI; gray-level difference statistics; macroscopic lesion white matter; magnetic resonance imaging; multiple sclerosis; normal appearing white matter; texture analysis; Entropy; Feature extraction; Image texture analysis; Lesions; Magnetic analysis; Magnetic resonance; Magnetic resonance imaging; Multiple sclerosis; Statistical analysis; Statistics; Gray-level difference statistics; MRI; Multiple sclerosis; Texture analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Education Technology and Computer Science, 2009. ETCS '09. First International Workshop on
Conference_Location
Wuhan, Hubei
Print_ISBN
978-1-4244-3581-4
Type
conf
DOI
10.1109/ETCS.2009.708
Filename
4959425
Link To Document