학술논문
Automatic Detection of Lumbar Disc Herniation Using YOLOv7
Document Type
Conference
Author
Source
2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan) Consumer Electronics - Taiwan (ICCE-Taiwan), 2023 International Conference on. :843-844 Jul, 2023
Subject
Language
ISSN
2575-8284
Abstract
The detection of lumbar disc herniation (LDH) through magnetic resonance imaging (MRI) poses a challenge due to the various shapes, sizes, angles, and regions associated with bulges, protrusions, extrusions, and sequestrations. One potential solution is using deep learning methods to identify lumbar abnormalities in MRI images automatically. The YOU ONLY LOOK ONCE (YOLO) model series has gained popularity for training deep learning algorithms for real-time biomedical image detection. This study aims to assess the performance of the latest YOLOv7 in detecting LDH across different regions of the lumbar intervertebral disc. The analysis revealed that YOLOv7 exhibits a poor performance and low detection rate of LDH across the L1-L2, L2-L3, L3-L4, L4-L5, and L5-S1 regions.