Nerve recognition in percutaneous transforaminal endoscopic discectomy using convolutional neural network. Issue 5 (1st April 2021)
- Record Type:
- Journal Article
- Title:
- Nerve recognition in percutaneous transforaminal endoscopic discectomy using convolutional neural network. Issue 5 (1st April 2021)
- Main Title:
- Nerve recognition in percutaneous transforaminal endoscopic discectomy using convolutional neural network
- Authors:
- Cui, Peng
Shu, Tao
Lei, Jun
Chen, Wenxi - Abstract:
- Abstract : Purpose: Percutaneous transforaminal endoscopic discectomy (PTED) is one of the most common minimally invasive surgery methods used in clinic in recent years. In this study, we developed a computer‐aided detection system (CADS) based on convolutional neural network (CNN) to automatically recognize nerve and dura mater images under PTED surgery. Methods: We collected surgical videos from 65 patients with lumbar disc herniation who underwent PTED; we then converted the videos into images, and randomly divided some images into a training dataset, a validation dataset, test dataset. The training dataset and validation dataset were composed of 10 454 images containing nerve and dura mater from 50 randomly selected patients; test dataset contained 12 000 images from the remaining 15 patients. Results: The results showed that sensitivity, specificity, and accuracy reached 90.90%, 93.68%, and 92.29%, respectively. CADS could recognize the nerve and dura mater with no significant difference ( P > 0.05) between each patient in test dataset. In comparison with clinicians of different levels, the performance of CADS was lower than that of a spinal endoscopist, but significantly higher than that of general surgeons. With the assistance of CADS, the performance of the general surgeons approached that of the spinal endoscopist. Conclusions: CNN can recognize well nerve and dura mater images in PTED surgery, and can help general surgeons to improve their ability to recognizeAbstract : Purpose: Percutaneous transforaminal endoscopic discectomy (PTED) is one of the most common minimally invasive surgery methods used in clinic in recent years. In this study, we developed a computer‐aided detection system (CADS) based on convolutional neural network (CNN) to automatically recognize nerve and dura mater images under PTED surgery. Methods: We collected surgical videos from 65 patients with lumbar disc herniation who underwent PTED; we then converted the videos into images, and randomly divided some images into a training dataset, a validation dataset, test dataset. The training dataset and validation dataset were composed of 10 454 images containing nerve and dura mater from 50 randomly selected patients; test dataset contained 12 000 images from the remaining 15 patients. Results: The results showed that sensitivity, specificity, and accuracy reached 90.90%, 93.68%, and 92.29%, respectively. CADS could recognize the nerve and dura mater with no significant difference ( P > 0.05) between each patient in test dataset. In comparison with clinicians of different levels, the performance of CADS was lower than that of a spinal endoscopist, but significantly higher than that of general surgeons. With the assistance of CADS, the performance of the general surgeons approached that of the spinal endoscopist. Conclusions: CNN can recognize well nerve and dura mater images in PTED surgery, and can help general surgeons to improve their ability to recognize tissues during the operation. … (more)
- Is Part Of:
- Medical physics. Volume 48:Issue 5(2021)
- Journal:
- Medical physics
- Issue:
- Volume 48:Issue 5(2021)
- Issue Display:
- Volume 48, Issue 5 (2021)
- Year:
- 2021
- Volume:
- 48
- Issue:
- 5
- Issue Sort Value:
- 2021-0048-0005-0000
- Page Start:
- 2279
- Page End:
- 2288
- Publication Date:
- 2021-04-01
- Subjects:
- computer‐aided detection -- convolutional neural network -- percutaneous transformational endoscopic discectomy -- tissue recognize
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610.153 - Journal URLs:
- http://scitation.aip.org/content/aapm/journal/medphys ↗
https://aapm.onlinelibrary.wiley.com/journal/24734209 ↗
http://www.aip.org/ ↗ - DOI:
- 10.1002/mp.14822 ↗
- Languages:
- English
- ISSNs:
- 0094-2405
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - 5531.130000
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