An effective Alzheimer’s disease segmentation and classification using Deep ResUnet and Efficientnet-Reference-Cited by-同舟云学术

An effective Alzheimer’s disease segmentation and classification using Deep ResUnet and Efficientnet

Published:2023-12-20 Issue: Volume: Page:1-12
ISSN:0739-1102
Container-title:Journal of Biomolecular Structure and Dynamics
language:en
Short-container-title:Journal of Biomolecular Structure and Dynamics

Author:

Rao Battula Srinivasa¹,Aparna Mudiyala¹,Harikiran Jonnadula¹,Reddy Tatireddy Subba²

Affiliation:

1. School of Computer Science and Engineering, VIT-AP University, Amravathi, India

2. Department of Computer Science and Engineering, B V Raju Institute of Technology, Narsapur, India

Publisher

Informa UK Limited

Subject

Molecular Biology,General Medicine,Structural Biology

Link

https://www.tandfonline.com/doi/pdf/10.1080/07391102.2023.2294381

Reference35 articles.

1. CAD-ALZ: A Blockwise Fine-Tuning Strategy on Convolutional Model and Random Forest Classifier for Recognition of Multistage Alzheimer’s Disease

2. DAD-Net: Classification of Alzheimer’s Disease Using ADASYN Oversampling Technique and Optimized Neural Network

3. Brain MRI Analysis for Alzheimer’s Disease Diagnosis Using CNN-Based Feature Extraction and Machine Learning

4. Multiplane ConVolutional Neural Network (Mp-CNN) for Alzheimer’s disease classification;Angkoso C. V.;International Journal of Intelligent Engineering and Systems,,2022

5. Hybridized Deep Learning Approach for Detecting Alzheimer’s Disease

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