Article: CNN-based detection of cervical spinal cord injury Journal: International Journal of Medical Engineering and Informatics (IJMEI) 2025 Vol.17 No.6 pp.513 - 525 Abstract: Magnetic resonance imaging (MRI) has the ability to infer alterations on a microscopic level in lesions that are present on the spinal cord. For the purpose of locating lesions brought on by cervical illnesses, our deep neural network using MRI was suggested. The segmentation of spine pictures, as well as their identification, diagnosis, as well as quantitative assessment, have all seen significant applications of the deep learning technology. The most cutting-edge approach to machine learning using medical imaging data is called convolutional neural networks (CNNs), which are powered by deep learning. The proposed network produces segmentation results that are in high degree of agreement with the real world situation. The suggested network produces outstanding results on testing. These findings are based upon that pixel level. The machine learning network that was suggested is both efficient and reliable for doing completely autonomous segmentation of the problematic area. Inderscience Publishers - linking academia, business and industry through research

Title: CNN-based detection of cervical spinal cord injury

Authors: G. Chandraiah; K. Mekala Devi; A. Mohamed Abbas; S. Rajalakshmi

Addresses: Department of Electronics and Communication Engineering, Sri Venkateswara Engineering College, Tirupati, Andhra Pradesh, 517502, India ' Department of Electronics and Communication Engineering, S.A. Engineering College, Chennai – 600077, India ' Department of Electronics and Communication Engineering, Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai – 600062, India ' Department of Computer Science and Engineering, Sri Venkateswara College of Engineering, Pennalur, Sriperumbudur – 602117, India

Abstract: Magnetic resonance imaging (MRI) has the ability to infer alterations on a microscopic level in lesions that are present on the spinal cord. For the purpose of locating lesions brought on by cervical illnesses, our deep neural network using MRI was suggested. The segmentation of spine pictures, as well as their identification, diagnosis, as well as quantitative assessment, have all seen significant applications of the deep learning technology. The most cutting-edge approach to machine learning using medical imaging data is called convolutional neural networks (CNNs), which are powered by deep learning. The proposed network produces segmentation results that are in high degree of agreement with the real world situation. The suggested network produces outstanding results on testing. These findings are based upon that pixel level. The machine learning network that was suggested is both efficient and reliable for doing completely autonomous segmentation of the problematic area.

Keywords: analysis of the spine province; magnetic resonance imaging; MRI; spinal cord; convolutional neural networks; CNNs.

DOI: 10.1504/IJMEI.2025.149549

International Journal of Medical Engineering and Informatics, 2025 Vol.17 No.6, pp.513 - 525

Received: 01 Sep 2022
Accepted: 19 Dec 2022
Published online: 07 Nov 2025 *

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Title: CNN-based detection of cervical spinal cord injury

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