Soft Attention Based DenseNet Model for Parkinson’s Disease Classification Using SPECT Images

Soft Attention Based DenseNet Model for Parkinson’s Disease Classification Using SPECT Images

ObjectiveDeep learning algorithms have long been involved in the diagnosis of severe neurological disorders that interfere with patients’ everyday tasks, such as Parkinson’s disease (PD). The most effective imaging modality for detecting the condition is DaTscan, a variety of single-photon emission...

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Bibliographic Details
Main Authors: Mahima Thakur, Harisudha Kuresan, Samiappan Dhanalakshmi, Khin Wee Lai, Xiang Wu
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-07-01
Series:Frontiers in Aging Neuroscience
Subjects:
neural networks
Parkinson’s disease (PD)
DenseNet architecture
region of convergence (ROC)
area under the curve
Online Access:https://www.frontiersin.org/articles/10.3389/fnagi.2022.908143/full

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https://www.frontiersin.org/articles/10.3389/fnagi.2022.908143/full

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