Lumbar Spine Degeneration Detection Using MRI Images
Year: 2025
Type: article
Abstract: This study presents a deep learning-based system for classifying lumbar spine degeneration using MRI images. A hybrid Convolutional Neural Network (CNN) and Multi-Layer Perceptron (MLP) model was developed, integrating image-based features and coordinate data to detect the severity of Left Subarticular Stenosis. Transfer Learning techniques, including DenseNet, ResNet, and VGG16, were explored for performance enhancement. The model was evaluated using multiple metrics such as accuracy, precision, recall, AUC-ROC, and F1-score. Results indicate that the custom CNN-MLP hybrid model offers improved diagnostic accuracy compared to traditional methods. The findings emphasize the growing role of deep learning in automated medical image analysis.
Authors: L, Ravi Teja, Chevuri, Govardhan Reddy, Chundi, Samba Sivuni Sai Kiran
Institution: VIT-AP University
Language: English
Topic: Medical Imaging and Analysis
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6893213972
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