In Ophthalmic surgery, lasers & imaging retina
BACKGROUND AND OBJECTIVE : The purpose of this study was to evaluate the accuracy and the time to find a lesion, taken in different platforms, color fundus photographs and infrared scanning laser ophthalmoscope images, using the traditional side-by-side (SBS) colocalization technique to an artificial intelligence (AI)-assisted technique.
PATIENTS AND METHODS : Fifty-three pathological lesions were studied in 11 eyes. Images were aligned using SBS and AI overlaid methods. The location of each color fundus lesion on the corresponding infrared scanning laser ophthalmoscope image was analyzed twice, one time for each method, on different days, for two specialists, in random order. The outcomes for each method were measured and recorded by an independent observer.
RESULTS : The colocalization AI method was superior to the conventional in accuracy and time (P < .001), with a mean time to colocalize 37% faster. The error rate using AI was 0% compared with 18% in SBS measurements.
CONCLUSIONS : AI permitted a more accurate and faster colocalization of pathologic lesions than the conventional method. [Ophthalmic Surg Lasers Imaging Retina 2023;54:108-113.].
Cavichini Melina, Bartsch Dirk-Uwe G, Warter Alexandra, Singh Sumit, An Cheolhong, Wang Yiqian, Zhang Junkang, Nguyen Truong, Freeman William R
2023-Feb
