Inflammation Segmentation Module using Convolution Neural Network for Alzheimer's Disease Detection using Magnetic Resonance Imaging Inputs-Reference-Cited by-同舟云学术

Inflammation Segmentation Module using Convolution Neural Network for Alzheimer's Disease Detection using Magnetic Resonance Imaging Inputs

Published:2024-04-04 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)
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Author:

Shetty Sahana¹,S Ramesh²,Nithya R³,Thangaraj P.⁴,J Antony Vijay⁵,K Sangamithrai⁶

Affiliation:

1. School of CSE, FET - Jain,Department of CSE-AIML and Cyber Security,Bangalore,India

2. College of Engineering & Technology, SRM Institute of Science and Technology,Department of Computing Technologies,Kattankulathur,Tamilnadu,India

3. Bannari Amman Institute of Technology,Department of CSE,Erode,Tamilnadu,India

4. Builders Engineering College,Department of CSE,Tirupur Dt,Tamilnadu,India

5. Karpagam College of Engineering,Department of CSE,Coimbatore,Tamilnadu,India

6. Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University,Department of Computer Science,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10568576/10568577/10568639.pdf?arnumber=10568639

Reference22 articles.

1. Volumetric Feature-Based Alzheimer’s Disease Diagnosis From sMRI Data Using a Convolutional Neural Network and a Deep Neural Network

2. Explainable Deep-Learning-Based Diagnosis of Alzheimer’s Disease Using Multimodal Input Fusion of PET and MRI Images

3. Agglomeration of deep learning networks for classifying binary and multiclass classifications using 3D MRI images for early diagnosis of Alzheimer’s disease: a feature-node approach

4. A Review of Deep Transfer Learning Approaches for Class-Wise Prediction of Alzheimer’s Disease Using MRI Images

5. Deep learning based diagnosis of Alzheimer’s disease using FDG-PET images