MORE | Spring 2019

Deep Learning of Brain Images for Classifying High-Risk Alzheimer’s Disease Population

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Researchers investigated that current methods for clinical diagnosis of AD are suboptimal. In recent years, the application of deep learning techniques to AD diagnosis has been broadly investigated due to its potentials of accurate and object diagnosis. To apply deep learning technique to AD diagnosis by the application of the transfer learning the technique, which borrows DL methods trained by other types of images and classifying medical images of interest. This study proposes a novel deep learning approach for analyzing MRI brain image data, which diagnoses AD based on features from voxel-based information.

Student researcher

Harshil Ketankumar Champaneria

Industrial engineering

Hometown: TEMPE, AZ, United States

Graduation date: Spring 2020

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