Automatic CDR Estimation for Early Glaucoma Diagnosis

Table 1

Model performance evaluation under Dataset1 database. The three classes are background (class 1), optic disc (class 2), and cup (class 3). (a) Simple tree, (b) bagged trees, (c) KNN, (d) complex tree, (e) linear discriminant, and (f) quadratic discriminant.

Indicator	a (%)	b (%)	c (%)	d (%)	e (%)	f (%)
Accuracy	95.54	98.66	97.22	96.63	85.55	89.11
Class-wise-averaged accuracy	82.70	95.02	89.39	86.99	53.28	61.39
Sensitivity class 1	98.17	99.61	99.31	98.88	90.59	95.19
Sensitivity class 2	74.35	91.75	82.23	79.16	46.84	40.70
Sensitivity class 3	77.21	90.63	78.94	79.55	46.42	45.16
Specificity class 1	89.43	96.20	91.24	90.90	74.78	63.71
Specificity class 2	97.29	99.23	98.61	98.07	91.73	94.56
Specificity class 3	99.23	99.80	99.50	99.43	95.93	98.23
PPV class 1	98.62	99.51	98.87	98.82	96.52	95.29
PPV class 2	69.30	90.74	82.91	77.12	31.77	38.07
PPV class 3	80.17	94.83	86.40	85.04	31.55	50.81
NPV class 1	86.35	96.93	94.51	91.30	50.76	63.20
NPV class 2	97.88	99.32	98.54	98.28	95.45	95.10
NPV class 3	99.08	99.62	99.15	99.18	97.79	97.79