眼底病变OCT图像的轻量化识别算法

侯小虎,贾晓芬,赵佰亭

Lightweight recognition algorithm for OCT images of fundus lesions

Xiao-hu HOU,Xiao-fen JIA,Bai-ting ZHAO

表 3 不同模型在Duke数据集上的对比实验结果

Tab.3 Experimental results of performance comparison of different models in Duke dataset

模型 图片类别 P/% R/% Spe/% Acc/% NP/106 OAcc/% Multiscale CNN[9] AMD 93.75 100 — 100 1.35 96.66 DME — — — — 正常眼底 100 93.33 — 93.33 Transfer Learning+SMA[10] AMD 100 100 100 100 — 99.89 DME 99.69 100 99.84 99.89 正常眼底 100 99.76 100 99.89 Resnet18[12] AMD 99.72 99.58 99.92 99.84 11.18 99.75 DME 99.80 99.72 99.92 99.84 正常眼底 99.70 99.84 99.78 99.80 MB-CNN AMD 100 99.7 100 99.2 1.35 99.92 DME 99.8 100 99.2 99.2 正常眼底 100 100 100 100