Details

Autor(en) / Beteiligte

• Sujatha Kumari, B. A.
• Yadiyala, A. G. Varun
• Aruna, B. J.
• Radha, C.
• Shwetha, B.

Titel

Early Detection of Mild Cognitive Impairment Using 3D Wavelet Transform

Ist Teil von

• Data Intelligence and Cognitive Informatics, 2021, p.445-455

Ort / Verlag

Singapore: Springer Singapore Pte. Limited

Erscheinungsjahr

2021

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Dementia is the brain disorder that effects the mental cognitive function. Dementia has different stages, namely C normal cognitive (CN), mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Mild cognitive impairment causes turn down in conscious thought and thinking ability. A person with MCI is at an increased risk of developing Alzheimer’s disease. Hence, it is important to determine AD at an earlier stage which is mild cognitive impairment (MCI) as toxic changes may start in the brain at the beginning stage of the Alzheimer’s disease. The proposed work is to detect MCI using MRI images. Firstly, the data samples are subjected to segmentation from which the 3D images of grey matter of each MRI sample are extracted. Then, the resulting images are pre-processed using 3D wavelet transform (DWT) which is fed to a machine learning classifier. The proposed work includes unique and efficient hybrid machine learning algorithm to classify between CN, MCI and AD subjects.