CORONAL SLICES SEGMENTATION OF MRI IMAGES USING ACTIVE CONTOUR METHOD ON INITIAL IDENTIFICATION OF ALZHEIMER SEVERITY LEVEL BASED ON CLINICAL DEMENTIA RATING (CDR)

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Wos IDWOS:000470092500039
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TitleCORONAL SLICES SEGMENTATION OF MRI IMAGES USING ACTIVE CONTOUR METHOD ON INITIAL IDENTIFICATION OF ALZHEIMER SEVERITY LEVEL BASED ON CLINICAL DEMENTIA RATING (CDR)
First Author
Last Author
AuthorsSupriyanti, R; Subhi, AR; Ramadhani, Y; Widodo, HB;
Publish DateJUN 2019
Journal NameJOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY
Citation
AbstractAlzheimer's is a type of syndrome disease with apoptosis of brain cells at about the same time, so the brain appears to shrivel and shrink. This condition causes the nerve cell cells in the brain to die, so the brain signal is difficult to transmit well. To find out the size of brain changes, the most commonly used equipment among physicians is the Magnetic Resonance Imaging (MRI) machine that produces medical images. The main purpose of this research is to segment the MRI brain image to identify the severity of Alzheimer based on the Clinical Dementia Rating (CDR) value. It's just because the image MRI itself consists of 3 slices of coronal, sagittal and axial, then in this paper, we only discuss coronal slices only. Segmentation will be done in the hippocampal and ventricular areas using active contour method. In this research, we only focus on measuring the area shown on the number of pixels in the two segmentation areas. Furthermore, it will automatically identify the number of segmentation pixels in the Alzheimer population based on the CDR value. Visualization of hippocampal and ventricular cells is done by segmenting the image pieces obtained from the OASIS (Open Access Series of Image Studies) database. The results show that the normal image of a hippocampal object has a pixel range of 148-296 pixels and abnormal images are in the range of 68-144 pixels, while ventricular objects have ranges of 50 to 472 pixels for normal imagery and 473-899 pixels for abnormal images.
Publish TypeJournal
Publish Year2019
Page Begin1672
Page End1686
Issn
Eissn1823-4690
Urlhttps://www.webofscience.com/wos/woscc/full-record/WOS:000470092500039
AuthorDr RETNO SUPRIYANTI, S.T, M.T
File124058.pdf