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IDA-Net: Inheritable Deformable Attention Network of structural MRI for Alzheimer’s Disease Diagnosis by Qin Zhao; Guoheng Huang; Pingping Xu; Ziyang Chen; Wenyuan Li; Xiaochen Yuan; Guo Zhong; Chi-Man Pun; Zhixin Huang is a Medicine article available to read on EtoBox.

What is IDA-Net: Inheritable Deformable Attention Network of structural MRI for Alzheimer’s Disease Diagnosis about?

To precisely diagnose neurological diseases, such as Alzheimer's disease, clinicians need to observe the microstructural changes of local brain atrophy with the help of structural magnetic resonance image (sMRI). Some Convolutional Neural Networks (CNNs) have recently achieved excellent performance in auxiliary clinicians to provide the diagnosis suggestion. However, there still exist several challenges. Foremost, several researchers manually predefine some regions of interest (ROIs) as the input of the CNN-based networks, which impedes the model's robustness and interpretability of clinical applications. Second, since the position relevance of pathological features interferes with the surrounding tissue regions in ROIs, it is hard for the current CNN-based networks to extract the microstructural changes of these ROIs precisely. To address the above challenges, we optimize the Transformer structure for Alzheimer's Disease Diagnosis and propose an Inheritable Deformable Attention Network (IDA-Net). Specifically, the IDA-Net mainly comprises the 3D Deformable Self-Attention module and the Inheritable 3D Deformable Self-Attention module. The 3D Deformable Self-Attention module can aut

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Author

Qin Zhao; Guoheng Huang; Pingping Xu; Ziyang Chen; Wenyuan Li; Xiaochen Yuan; Guo Zhong; Chi-Man Pun; Zhixin Huang

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Medicine (Physical Sciences)