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Parkinson's Disease Detection with Ensemble Architectures based on ILSVRC Models
In this work, we explore various neural network architectures using Magnetic Resonance (MR) T1 images of the brain to identify Parkinson's Disease (PD), which is one of the most common neurodegenerative and movement disorders.
Parkinson's Disease Detection Using Ensemble Architecture from MR Images
We find that detection accuracy increases drastically when we focus on the Gray Matter (GM) and White Matter (WM) regions from the MR images instead of using whole MR images.
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