. Author manuscript; available in PMC: 2019 Nov 27.

Published in final edited form as: IEEE Trans Biomed Eng. 2018 May;65(5):1151–1165. doi: 10.1109/TBME.2017.2787025

TABLE I.

Quantitative Measurements of the Proposed Method for Automatic Reconnection of Gaps on the 4 Validation Datasets

Datasets	Gap sizes	Iterations	N_BP	N_AP	SR	Sensitivity		Specificity		DC		MCC
						BP	AP	BP	AP	BP	AP	BP	AP
DRIVE	λ = 7 × 7	1	4393	68	98.5%	0.9348	0.9959	1	0.9998	0.9663	0.9956	0.9656	0.9955
	λ = 11 × 11	2	4395	171	96.0%	0.8786	0.9894	1	0.9994	0.9353	0.9874	0.9351	0.9869
	λ = 15 × 15	2	4161	335	92.0%	0.8219	0.9763	1	0.9990	0.9020	0.9756	0.9034	0.9747
IOSTAR	λ = 7 × 7	1	1932	14	99.4%	0.9393	0.9981	1	0.9997	0.9687	0.9942	0.9683	0.9940
	λ = 11 × 11	2	2006	30	98.5%	0.8859	0.9966	1	0.9997	0.9394	0.9936	0.9396	0.9934
	λ = 15 × 15	2	1845	88	95.3%	0.8354	0.9906	1	0.9996	0.9102	0.9878	0.9118	0.9874
HRF-Patch	λ = 15 × 15	1	410	9	98.0%	0.9123	0.9991	1	0.9999	0.9541	0.9973	0.9546	0.9972
	λ = 23 × 23	2	410	16	96.5%	0.8575	0.9936	1	0.9999	0.9231	0.9940	0.9252	0.9939
	λ = 31 × 31	2	410	32	92.8%	0.8061	0.9862	1	0.9998	0.8924	0.9897	0.8967	0.9896
	λ = 39 × 39	3	410	44	89.7%	0.7533	0.9552	1	0.9997	0.8588	0.9643	0.8665	0.9639
Corneal Nerve Fiber	λ = 13 × 13	1	5278	23	99.6%	0.8962	0.9929	1	0.9998	0.9453	0.9895	0.9459	0.9894
	λ = 19 × 19	2	5278	113	98.0%	0.8383	0.9800	1	0.9992	0.9120	0.9647	0.9144	0.9643
	λ = 25 × 25	2	5278	316	94.0%	0.7838	0.9743	1	0.9991	0.8788	0.9594	0.8839	0.9589
	λ = 31 × 31	2	4251	674	85.0%	0.7820	0.9665	1	0.9991	0.8776	0.9529	0.8828	0.9522

BP: Before processing; AP: After processing; N_BP: Number of gaps before processing; N_AP: Number of gaps after processing; SR; Success rate; DC: Dice coefficient; MCC: Matthews correlation coefficient