DocumentCode :
3562599
Title :
Volumetric assessment of human brain morphology using pixel counting technique
Author :
Nithyakalyani, K. ; Kalpana, R. ; Vigneswaran, R.
Author_Institution :
Dept. of Biomed. Eng., Vel Tech Multi Tech Dr. R.R. Dr. S.R. Eng. Coll., Chennai, India
fYear :
2014
Firstpage :
1
Lastpage :
6
Abstract :
Morphometric measurements such as volume, thickness and sulcal depth are used to provide valuable information about cortical characteristics in both healthy and diseased conditions of the brain. Relevantly, the focus of this paper is to illustrate the morphometric method of assessing the volume changes in the brain caused by aging and/or pathological condition. Using the T1-weighted magnetic resonance images of the brain, the clustering technique is adopted towards segmenting the image into separate compartments of white and gray matters (WM and GM) and the cerebral-spinal fluid (CSF). The clustering technique pursued includes the traditional K-means and fuzzy C-means algorithm by considering the Euclidean distance metric toward grouping of entities of similar pattern vectors. The method evolved allows the underlying volume measurement of clustered regions by pixel-counting technique. Comparison of volume measurement of segmented cerebral tissues among male and female subjects undergoing ageing process and with cerebral pathogenic states is exercised. The results reveal distinct details thereof. Specifically, the volumetric assessment indicated proves to be a viable technique toward understanding the geriatric changes in the brain as well as the conditions of brain tissues vis-à-vis neuro-related issues. Clinical data gathered and computed results on the proposed method are furnished to illustrate the efficacy of the method and its short comings.
Keywords :
biomedical MRI; biomedical measurement; brain; fuzzy systems; geriatrics; image segmentation; medical image processing; neurophysiology; volume measurement; Euclidean distance metric; K-means algorithm; T1-weighted brain MR image; T1-weighted magnetic resonance image; ageing process; aging-caused brain volume changes; brain CSF; brain GM; brain WM; brain cortical characteristics; brain gray matters; brain image segmentation; brain morphology volumetric assessment; brain sulcal depth measurement; brain thickness measurement; brain tissue conditions; brain volume changes assessment; brain volume measurement; brain white matter; cerebral pathogenic states; cerebral-spinal fluid; clustered region volume measurement; clustering technique; diseased brain conditions; fuzzy C-means algorithm; geriatric brain changes; healthy brain conditions; human brain morphology; morphometric measurements; morphometric method; neuro-related conditions; pathological condition-caused brain volume changes; pixel counting technique; segmented cerebral tissue image; segmented female cerebral tissue image; segmented male cerebral tissue image; similar pattern vectors; Aging; Brain; Clustering algorithms; Euclidean distance; Image segmentation; Lesions; Volume measurement; Cerebrospinal fluid; Gray matter; K-means and Fuzzy C-means clustering technique; Pixel counting technique; White matter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Science Engineering and Management Research (ICSEMR), 2014 International Conference on
Print_ISBN :
978-1-4799-7614-0
Type :
conf
DOI :
10.1109/ICSEMR.2014.7043556
Filename :
7043556
Link To Document :
بازگشت