Development and Validation of Automated Visual Field Report Extraction Platform Using Computer Vision Tools

• Published in: Frontiers in medicine 2021-04, Vol.8, p.625487-625487
• Main Authors: Saifee, Murtaza, Wu, Jian, Liu, Yingna, Ma, Ping, Patlidanon, Jutima, Yu, Yinxi, Ying, Gui-Shuang, Han, Ying
• Format: Article
• Language: English
• Subjects: computer vision and image processing; glaucoma; Medicine; neuroophthalmogy; optical character reader; visual field
• ISSN: 2296-858X; 2296-858X
• DOI: 10.3389/fmed.2021.625487

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. 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. 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,