机构:[1]Department of Ophthalmology, University of California, San Francisco, San Francisco, CA, United States,[2]Beijing Ophthalmology and Visual Science Key Lab, Beijing Tongren Eye Center, Beijing Tongren Hospital, Beijing Institute of Ophthalmology, Capital Medical University, Beijing, China,研究所眼科研究所首都医科大学附属北京同仁医院首都医科大学附属同仁医院[3]Department of Ophthalmology, Shandong Provincial Hospital, Shandong First Medical University, Jinan, China,[4]Department of Ophthalmology, Bhumibol Adulyadej Hospital, Bangkok, Thailand,[5]Center for Preventive Ophthalmology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States,[6]Ophthalmology Section, Surgical Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, United States
Purpose: To introduce and validate hvf_extraction_script, an open-source software script for the automated extraction and structuring of metadata, value plot data, and percentile plot data from Humphrey visual field (HVF) report images. Methods: Validation was performed on 90 HVF reports over three different report layouts, including a total of 1,530 metadata fields, 15,536 value plot data points, and 10,210 percentile data points, between the computer script and four human extractors, compared against DICOM reference data. Computer extraction and human extraction were compared on extraction time as well as accuracy of extraction for metadata, value plot data, and percentile plot data. Results: Computer extraction required 4.9-8.9 s per report, compared to the 6.5-19 min required by human extractors, representing a more than 40-fold difference in extraction speed. Computer metadata extraction error rate varied from an aggregate 1.2-3.5%, compared to 0.2-9.2% for human metadata extraction across all layouts. Computer value data point extraction had an aggregate error rate of 0.9% for version 1, <0.01% in version 2, and 0.15% in version 3, compared to 0.8-9.2% aggregate error rate for human extraction. Computer percentile data point extraction similarly had very low error rates, with no errors occurring in version 1 and 2, and 0.06% error rate in version 3, compared to 0.06-12.2% error rate for human extraction. Conclusions: This study introduces and validates hvf_extraction_script, an open-source tool for fast, accurate, automated data extraction of HVF reports to facilitate analysis of large-volume HVF datasets, and demonstrates the value of image processing tools in facilitating faster and cheaper large-volume data extraction in research settings.
基金:
NEI EY028747-01 funding to YH,NEI P30 EY002162 Core Grant
for Vision Research, and an unrestricted grant from Research to
Prevent Blindness, New York, NY.
第一作者机构:[1]Department of Ophthalmology, University of California, San Francisco, San Francisco, CA, United States,
通讯作者:
通讯机构:[1]Department of Ophthalmology, University of California, San Francisco, San Francisco, CA, United States,[6]Ophthalmology Section, Surgical Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, United States
推荐引用方式(GB/T 7714):
Saifee Murtaza,Wu Jian,Liu Yingna,et al.Development and Validation of Automated Visual Field Report Extraction Platform Using Computer Vision Tools[J].FRONTIERS IN MEDICINE.2021,8:doi:10.3389/fmed.2021.625487.
APA:
Saifee, Murtaza,Wu, Jian,Liu, Yingna,Ma, Ping,Patlidanon, Jutima...&Han, Ying.(2021).Development and Validation of Automated Visual Field Report Extraction Platform Using Computer Vision Tools.FRONTIERS IN MEDICINE,8,
MLA:
Saifee, Murtaza,et al."Development and Validation of Automated Visual Field Report Extraction Platform Using Computer Vision Tools".FRONTIERS IN MEDICINE 8.(2021)