Version 1
: Received: 2 September 2024 / Approved: 4 September 2024 / Online: 4 September 2024 (07:42:08 CEST)
How to cite:
Wu, C.-Y.; Yeh, W.-C.; Chang, S.-M.; Hsu, C.-W.; Lin, Z.-J. The Application of Deep Learning to Accurately Identify the Dimensions of Spinal Canal and Intervertebral Foramen as Evaluated by the IoU Index. Preprints2024, 2024090326. https://doi.org/10.20944/preprints202409.0326.v1
Wu, C.-Y.; Yeh, W.-C.; Chang, S.-M.; Hsu, C.-W.; Lin, Z.-J. The Application of Deep Learning to Accurately Identify the Dimensions of Spinal Canal and Intervertebral Foramen as Evaluated by the IoU Index. Preprints 2024, 2024090326. https://doi.org/10.20944/preprints202409.0326.v1
Wu, C.-Y.; Yeh, W.-C.; Chang, S.-M.; Hsu, C.-W.; Lin, Z.-J. The Application of Deep Learning to Accurately Identify the Dimensions of Spinal Canal and Intervertebral Foramen as Evaluated by the IoU Index. Preprints2024, 2024090326. https://doi.org/10.20944/preprints202409.0326.v1
APA Style
Wu, C. Y., Yeh, W. C., Chang, S. M., Hsu, C. W., & Lin, Z. J. (2024). The Application of Deep Learning to Accurately Identify the Dimensions of Spinal Canal and Intervertebral Foramen as Evaluated by the IoU Index. Preprints. https://doi.org/10.20944/preprints202409.0326.v1
Chicago/Turabian Style
Wu, C., Che-Wei Hsu and Zi-Jie Lin. 2024 "The Application of Deep Learning to Accurately Identify the Dimensions of Spinal Canal and Intervertebral Foramen as Evaluated by the IoU Index" Preprints. https://doi.org/10.20944/preprints202409.0326.v1
Abstract
Artificial intelligence has garnered significant attention in recent years as a rapidly advancing field of computer technology. With the continual advancement of computer hardware, deep learning has made breakthrough developments within the realm of artificial intelligence. Over the past few years, applying deep learning architecture in medicine and Industrial anomaly inspection has significantly contributed to solving numerous challenges related to efficiency and accuracy. Despite excellent results in radiological, pathological, endoscopic, ultrasonic, and biochemical examinations, this paper utilizes deep learning combined with image processing to identify spinal canal and vertebral foramen dimensions. In existing research, technologies such as corrosion and expansion in magnetic resonance image (MRI) processing have also strengthening the accuracy of results. Indicators such as area and Intersection over Union (IoU)are also provided for assessment. Among them, the mean average precision (mAP), for identifying intervertebral foramen (IVF) and intervertebral disc (IVD) through YOLOv4 is 95.6%. Resnet50 mixing U-Net was employed to identify the spinal canal and intervertebral foramen and achieved IoU scores of 79.11% and 80.89%.
Keywords
artificial intelligence; deep learning; magnetic resonance image; vertebral foramen; intervertebral canal
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
