A curriculum learning-based fully automated system for quantification of the choroidal structure in highly myopic patients. (21st June 2022)
- Record Type:
- Journal Article
- Title:
- A curriculum learning-based fully automated system for quantification of the choroidal structure in highly myopic patients. (21st June 2022)
- Main Title:
- A curriculum learning-based fully automated system for quantification of the choroidal structure in highly myopic patients
- Authors:
- Liu, Xindi
Jin, Kai
Yang, Zehua
Yan, Yan
Wang, Shuai
Wang, Yaqi
Ye, Juan - Abstract:
- Abstract: Objective. An automated tool for choroidal segmentation and quantitative analysis under pathological conditions is currently lacking, hindering the exploration of choroidal structural changes in fundus diseases. This study aims to create a fully automated deep learning system for the quantitative analysis of the choroid with pathological changes, and to apply the system in analyzing the correlation between the choroidal structure and the severity of high myopia. Approach . A total of 2590 optical coherence tomography B-scan images of 1424 eyes of 1029 patients of high myopia from 3 hospitals were collected. We developed a curriculum learning-based system, including a two-stage U-net (TSU-net) and a post-process module for segmentation of the choroid, to calculate mean choroidal thickness (MCT) and choroidal vascularity index (CVI). The output of the images was statistically analyzed to explore the associations among MCT, CVI and the clinical characteristics of the patients. Main results . The Dice coefficient and IoU measures of choroid segmentation were 0.9221 and 0.8575, respectively. In a human-machine comparison, the system performed faster and better than a senior ophthalmologist. Statistical analysis demonstrated that, MCT is correlated with age, scan region, axial length, maculopathy type, and CVI, and CVI is correlated with scan region and MCT. Significance . A fully automated choroidal structural quantification system was developed. Clinical evaluationAbstract: Objective. An automated tool for choroidal segmentation and quantitative analysis under pathological conditions is currently lacking, hindering the exploration of choroidal structural changes in fundus diseases. This study aims to create a fully automated deep learning system for the quantitative analysis of the choroid with pathological changes, and to apply the system in analyzing the correlation between the choroidal structure and the severity of high myopia. Approach . A total of 2590 optical coherence tomography B-scan images of 1424 eyes of 1029 patients of high myopia from 3 hospitals were collected. We developed a curriculum learning-based system, including a two-stage U-net (TSU-net) and a post-process module for segmentation of the choroid, to calculate mean choroidal thickness (MCT) and choroidal vascularity index (CVI). The output of the images was statistically analyzed to explore the associations among MCT, CVI and the clinical characteristics of the patients. Main results . The Dice coefficient and IoU measures of choroid segmentation were 0.9221 and 0.8575, respectively. In a human-machine comparison, the system performed faster and better than a senior ophthalmologist. Statistical analysis demonstrated that, MCT is correlated with age, scan region, axial length, maculopathy type, and CVI, and CVI is correlated with scan region and MCT. Significance . A fully automated choroidal structural quantification system was developed. Clinical evaluation demonstrated that severity of high myopia is closely related to MCT but shows only a low correlation with CVI, suggesting that CVI may have little applicability in eyes with large anatomical structural variations. Future quantitative analysis of choroidal structure of large samples will enable exploration of the pathogenesis of additional fundus diseases. … (more)
- Is Part Of:
- Physics in medicine & biology. Volume 67:Number 12(2022)
- Journal:
- Physics in medicine & biology
- Issue:
- Volume 67:Number 12(2022)
- Issue Display:
- Volume 67, Issue 12 (2022)
- Year:
- 2022
- Volume:
- 67
- Issue:
- 12
- Issue Sort Value:
- 2022-0067-0012-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-06-21
- Subjects:
- high myopia -- choroidal structure -- optical coherence tomography -- deep learning -- segmentation
Biophysics -- Periodicals
Medical physics -- Periodicals
610.153 - Journal URLs:
- http://ioppublishing.org/ ↗
http://iopscience.iop.org/0031-9155 ↗ - DOI:
- 10.1088/1361-6560/ac749b ↗
- Languages:
- English
- ISSNs:
- 0031-9155
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 21958.xml