RT Journal Article SR Electronic T1 Efficacy of automated computer-aided diagnosis of retinal nerve fibre layer defects in healthcare screening JF British Journal of Ophthalmology JO Br J Ophthalmol FD BMJ Publishing Group Ltd. SP 295 OP 298 DO 10.1136/bjophthalmol-2015-307527 VO 101 IS 3 A1 Sang Beom Han A1 Hee Kyung Yang A1 Ji Eun Oh A1 Kwang Gi Kim A1 Jeong-Min Hwang YR 2017 UL http://bjo.bmj.com/content/101/3/295.abstract AB Background/aims To evaluate the efficacy of a new automatic computer-aided detection (CAD) system for mass screening of retinal nerve fibre layer (RNFL) defects in a large population using fundus photographs.Methods Among the fundus photographs of 1200 consecutive subjects who visited a healthcare centre, a total of 2270 photographs appropriate for analysis were tested. The photographs were first reviewed by two expert ophthalmologists for detection of RNFL defects (gold standard manual detection). The images were then analysed using an automatic CAD system for detecting RNFL defects in various cases of glaucomatous and non-glaucomatous optic neuropathy. A free-response receiver operating characteristics curve was generated to evaluate the validity of the CAD system. The results of the automatic detection were compared with those of manual detection, and sensitivity and specificity of the CAD system were calculated.Results In manual detection of 2270 photographs, 41 RNFL defects from 36 photographs (1.6%) were detected, and no RNFL defects were found in 2234 photographs (98.4%). The sensitivity of the CAD system for detecting RNFL defects was 90.2% (37/41 RNFL defects) and the specificity was 72.5% (1620/2234 photographs with no RNFL defects) at a false-positive rate of 0.36 per image.Conclusions The new CAD system successfully detected RNFL defects during mass screening of fundus photographs in a large population who visited a healthcare centre. The proposed algorithm can be useful for clinicians in screening RNFL defects in healthcare centres. The false-positive rate is still unsatisfactory, although improved compared with the previous study. Further studies are needed to enhance the speed and specificity of image analysis using the CAD system.