Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/15589
Title: Multi-Modal Mri Images Analysis for Improved Herniated Disc Diagnosis Using Deep Learning
Authors: Saji, Princy K
Krishnachalitha, K C
Kannan, M
Keywords: Deep Learning
Herniated Discs
MRI
Medical Industry
Healthcare Industry
Issue Date: 2024
Publisher: Medical Robotics and AI-Assisted Diagnostics for a High-Tech Healthcare Industry
IGI Global
Citation: pp. 65-80
Abstract: Herniated discs are a common medical condition that can cause severe back pain and lead to serious complications if not diagnosed and treated correctly. MRI is the preferred imaging modality for diagnosing herniated discs, providing detailed images of the spine and surrounding structures. A herniated disc, also known as a slipped or ruptured disc, occurs when the soft inner portion of a spinal disc protrudes through a tear in the more rigid outer layer. This can cause pain, numbness, and weakness in the affected area, typically the lower back or neck. The most common cause of a herniated disc is age-related degeneration of the spine, which can weaken the disc's outer layer and cause it to bulge or rupture. However, other factors such as improper lifting, repetitive strain, or trauma can also contribute to developing a herniated disc. Early detection of a herniated disc is vital because it allows for prompt treatment, preventing the condition from worsening and potentially causing permanent nerve damage. © 2024, IGI Global. All rights reserved.
URI: http://dx.doi.org/10.4018/979-8-3693-2105-8.ch005
http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/15589
ISBN: 9798369321065
9798369321058
Appears in Collections:Book/ Book Chapters

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