Automated Detection of Multiple Sclerosis Lesions in MRI with SegNet-Reference-Cited by-同舟云学术

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Automated Detection of Multiple Sclerosis Lesions in MRI with SegNet

Published:2023-12-29 Issue: Volume: Page:1-3
ISSN:
Container-title:2023 International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI)
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Author:

Varshney Neeraj¹,Agrawal Pankaj²,Rose Anthony³,Dewangan Deepak Kumar⁴,Singh Kamred Udham⁵,Somasekar J.⁶

Affiliation:

1. GLA University,Department of Computer Engineering & Apllications,Mathura,UP,India

2. Department Of Ele. & Tele. Raipur Institute Of Technology,Raipur

3. Institute of Management & Entrepreneurship Development, Bharati Vidyapeeth (Deemed to be University),Pune

4. Atal Bihari Vajpayee-Indian Institute of Information Technology and Management (ABV-IIITM),Department of Computer Science and Engineering,Gwalior

5. School of Computing, Graphic Era Hill University,Dehradun,India

6. Jain (Deemed-to-be University),Professor of CSE Department,Bangalore

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10488914/10488923/10489526.pdf?arnumber=10489526

Reference10 articles.

1. Artificial Neural Networks Identify the Predictive Values of Risk Factors on the Conversion of Amnestic Mild Cognitive Impairment

2. Diagnosis of Alzheimer’s Disease Using Dual-Tree Complex Wavelet Transform, PCA, and Feed-Forward Neural Network

3. MRI Segmentation of the Human Brain: Challenges, Methods, and Applications

4. Fully convolutional networks for semantic segmentation

5. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

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