Lombardi Lisa, Petoe Matthew A, Moussallem Lauren, Kolic Maria, Baglin Elizabeth K, Stefopoulos Samuel, Battiwalla Xerxes, Walker Janine G, Barnes Nick, Abbott Carla J, Allen Penelope J
Centre for Eye Research Australia, Royal Victorian Eye & Ear Hospital, East Melbourne, VIC, Australia.
Bionics Institute, East Melbourne, VIC, Australia.
Transl Vis Sci Technol. 2025 May 1;14(5):11. doi: 10.1167/tvst.14.5.11.
To compare accuracy of the comprehensive vision processing (VP) algorithm (Lanczos2 [L2]) with the novel VP algorithms, face detection (FaD) and available chair detection (ChD) methods in recipients of the second-generation suprachoroidal retinal prosthesis.
Four suprachoroidal retinal prosthesis recipients (#NCT05158049) were acclimatized to new VP methods (FaD and ChD) with L2 used as control. For face localization, one or two mannequins (white/black) were forward or backward facing in three positions in a room with a white backdrop. Participants were asked to detect the number of mannequins and faces present and point to the forward-facing mannequin. For available chair localization, two mannequins (white/black) were seated in two of three chairs (white/black). Participants were asked to detect and navigate to the available chair.
FaD performed significantly better than L2 for correct face detection (FaD) (81.25 ± 10.21%; L2 32.81 ± 5.98%; P = 0.029) and for face localization (FaD, 81.25 ± 10.21%; L2, 26.56 ± 10.67%; P = 0.029). The accuracy of mannequin detection was equivalent between FaD (47.22 ± 5.56%) and L2 (52.78 ± 13.98%) with one mannequin (P = 0.457), and with two mannequins present (FaD, 21.43 ± 18.44%; L2. 3.57 ± 7.14%; P = 0.257). The ChD VP method (88.89 ± 12.00% correct) performed significantly better than L2 (19.44 ± 13.22%) for localizing available chairs (P = 0.029).
FaD and ChD VP methods performed better than L2 for the purpose of localizing faces and available chairs, respectively.
New VP algorithms can improve the localization of specific object types while using the second-generation suprachoroidal retinal prosthesis.
比较综合视觉处理（VP）算法（Lanczos2 [L2]）与新型VP算法、面部检测（FaD）和可用椅子检测（ChD）方法在第二代脉络膜上视网膜假体接受者中的准确性。
四名脉络膜上视网膜假体接受者（#NCT05158049）适应新的VP方法（FaD和ChD），以L2作为对照。对于面部定位，在有白色背景的房间里，一个或两个模特（白色/黑色）在三个位置向前或向后摆放。要求参与者检测出现的模特和面部数量，并指向面向前方的模特。对于可用椅子定位，两个模特（白色/黑色）坐在三把椅子（白色/黑色）中的两把上。要求参与者检测并导航到可用椅子。
在正确面部检测（FaD）方面，FaD的表现明显优于L2（FaD为81.25±10.21%；L2为32.81±5.98%；P = 0.029），在面部定位方面也是如此（FaD为81.25±10.21%；L2为26.56±10.67%；P = 0.029）。在有一个模特时，FaD（47.22±5.56%）和L2（52.78±13.98%）的模特检测准确率相当（P = 0.457），当有两个模特时也是如此（FaD为21.43±18.44%；L2为3.57±7.14%；P = 0.257）。在定位可用椅子方面，ChD VP方法（正确率为88.89±12.00%）的表现明显优于L2（19.44±13.22%）（P = 0.029）。
FaD和ChD VP方法在面部和可用椅子定位方面分别比L2表现更好。
新的VP算法在使用第二代脉络膜上视网膜假体时可以改善特定物体类型的定位。
