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Alzheimer’s Detection at Early Stage Using Modified LGS (M-LGS) on MRI


Affiliations
1 Dept. of Computer Science & Engineering, Adi Shankara College of Engineering & Technology, Ernakulam, Kerala, India
2 Dept. of Information Technology, Higher College of Technology, Muscat, Oman
     

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Alzheimer’s Disease (AD) is the most common cause of dementia, which is a non-curable after a certain stage. The nerve cells, which are very essential to carry messages in the brain, particularly those responsible for storing memories, slowly get damaged due to the formation of tangles and plaques made from protein fragments in damaged areas of the brain. This paper focuses on early detection of Alzheimer’s disease using Magnetic Resonance Imaging (MRI), so that effective medication is possible. The minute changes in the Gray Matter (GM) and white is observed there in the MRI and the processing of this will be an aid to the expert for the correct diagnosis. The GM and WM are segmented from the image and the texture information is extracted using different variants of the Local Binary Pattern (LBP). It is observed that the Modified Local graph structure with the inclusion of grayscale information is a good descriptor for classifying AD and Mild Cognitive Impairment (MCI). The accuracy of the classification is improved by the inclusion of the proper threshold in the formation of local pattern.

Keywords

Alzheimer’s Disease, Local Patterns, Magnetic Resonance Imaging, Mild Cognitive Impairment, Normal Aging, Support Vector Machine.
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  • Alzheimer’s Detection at Early Stage Using Modified LGS (M-LGS) on MRI

Abstract Views: 271  |  PDF Views: 3

Authors

S. Nayaki K.
Dept. of Computer Science & Engineering, Adi Shankara College of Engineering & Technology, Ernakulam, Kerala, India
A. B. Varghese
Dept. of Information Technology, Higher College of Technology, Muscat, Oman

Abstract


Alzheimer’s Disease (AD) is the most common cause of dementia, which is a non-curable after a certain stage. The nerve cells, which are very essential to carry messages in the brain, particularly those responsible for storing memories, slowly get damaged due to the formation of tangles and plaques made from protein fragments in damaged areas of the brain. This paper focuses on early detection of Alzheimer’s disease using Magnetic Resonance Imaging (MRI), so that effective medication is possible. The minute changes in the Gray Matter (GM) and white is observed there in the MRI and the processing of this will be an aid to the expert for the correct diagnosis. The GM and WM are segmented from the image and the texture information is extracted using different variants of the Local Binary Pattern (LBP). It is observed that the Modified Local graph structure with the inclusion of grayscale information is a good descriptor for classifying AD and Mild Cognitive Impairment (MCI). The accuracy of the classification is improved by the inclusion of the proper threshold in the formation of local pattern.

Keywords


Alzheimer’s Disease, Local Patterns, Magnetic Resonance Imaging, Mild Cognitive Impairment, Normal Aging, Support Vector Machine.

References