Deep Learning Framework-Based Automated Multi-class Diagnosis for Neurological Disorders-Reference-Cited by-同舟云学术

Deep Learning Framework-Based Automated Multi-class Diagnosis for Neurological Disorders

Published:2023-08-04 Issue: Volume: Page:
ISSN:
Container-title:2023 7th International Conference on Automation, Control and Robots (ICACR)
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Author:

Ali Syed Saad Azhar¹,Memon Khuhed²,Yahya Norashikin²,Sattar Karim Asif³,El Ferik Sami⁴

Affiliation:

1. King Fahd University of Petroleum & Minerals,Interdisciplinary Research Center for Smart Mobility & Logistics Aerospace Engineering Department,Dhahran 31261,Saudi Arabia

2. Universiti Teknologi PETRONAS,Centre for Intelligent Signal & Imaging Research,Department of Electrical & Electronic Engineering,Seri Iskandar 32610,Perak,Malaysia

3. King Fahd University of Petroleum & Minerals,Interdisciplinary Research Center for Smart Mobility & Logistics,Dhahran 31261,Saudi Arabia

4. King Fahd University of Petroleum & Minerals,Interdisciplinary Research Center for Smart Mobility & Logistics Control & Instrumentation Engineering Department,Dhahran 31261,Saudi Arabia

Funder

King Fahd University of Petroleum and Minerals

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10314533/10314567/10314599.pdf?arnumber=10314599

Reference24 articles.

1. Classification of MRI brain images using combined wavelet entropy based spider web plots and probabilistic neural network

2. Exploring the reproducibility of functional connectivity alterations in Parkinson’s disease

3. Automated diagnosis of multi-class brain abnormalities using MRI images: A deep convolutional neural network based method

4. A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature selection