Year: 2024
Type: article
Abstract: : Chronic back pain caused by degenerative changes in the spinal disc has significantly impacted the quality of life of patients. Magnetic resonance imaging gives a very clear visualization of the intervertebral disc; however, it is still subjective and more mentally demanding when it is a manual assessment. Therefore, the present paper discusses the possibility of integrating image processing techniques with machine learning algorithms in order to arrive at more accurate diagnosis for spinal disc degeneration. Preprocessing the image, segmentation, and feature extraction are incorporated along with various machine learning models like convolutional neural networks (CNN) and support vector machines (SVM) into the review of present methodologies. Our results show that these hybrid approaches improve classification accuracy and aid in early detection for better management of the patient. This project helps in identifying the four stages of spinal disc degeneration.
Authors: Manisha Mali, Dhruv Aitwadekar, Swaraj Gaikwad, Rajat Deshmukh, Parth Choudhari, Aneesh Bhambure
Language: English
Topic: Medical Imaging and Analysis
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4404655804