Title :
Tagged cardiac MR image segmentation by contrast enhancement and texture analysis
Author :
Yang, Xiaomei ; Murase, Kenya
Author_Institution :
Coll. of Electr. Eng. & Inf. Technol., Sichuan Univ., Chengdu, China
Abstract :
Based on contrast enhancement and texture analysis, an automatic segmentation of the left ventricle in 2D tagged MR images is presented in this paper. Incorporating histogram modification and local contrast enhancement is applied as a method for improving contrast between tagged lines and non-tagged tissue. The ventricular blood filled and tagged regions are isolated by subtracting gray minimum from maximum within a small window. The feature value is large for textured region and small for homogeneous region. Media filter is used to effectively remove the influence of the tagged lines. Finally, GVF-snake model is applied to extract the boundary of the left ventricle. Experimental results show that the proposed method can effectively extract the endocardiac boundary of the left ventricle.
Keywords :
biomedical MRI; cardiology; image segmentation; image texture; median filters; medical image processing; 2D tagged MR images; GVF snake model; automatic left ventricle segmentation; gradient vector flow snake model; gray minimum subtraction; histogram modification; image contrast enhancement; image texture analysis; left ventricle endocardiac boundary; magnetic resonance imaging; median filter; tagged cardiac MR image segmentation; ventricular blood filled regions; Biomedical imaging; Filters; Histograms; Image analysis; Image motion analysis; Image segmentation; Image texture analysis; Information analysis; Myocardium; Tagging; contrast enhancement; image segmentation; tagged MR image; texture analysis;
Conference_Titel :
Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-3863-1
Electronic_ISBN :
978-1-4244-3864-8
DOI :
10.1109/ICEMI.2009.5274108
