计算和数学方法在医学
研究文章

探索结肠息肉的深度学习和转移学习分类

表8

精度的方法在% CC-i-Scan数据库。
方法 没有染色 染色
CVC i-Scan1 i-Scan2 i-Scan3 CVC i-Scan1 i-Scan2 i-Scan3
1:CNN-F 86.16 89.33 80.65 88.41 86.52 81.40 84.22 80.62 84.66
2:CNN-M 87.45 90.67 81.38 83.58 87.99 89.55 87.40 90.53 87.31
3:CNN-S 88.03 90.00 87.01 77.33 87.25 82.68 87.40 75.54 84.41
4:CNN-F m cn 88.84 82.00 73.15 90.73 85.78 89.55 89.72 83.15 85.36
5:CNN-M m cn 89.53 90.67 88.88 94.66 86.97 89.29 87.40 90.53 89.74
6:CNN-S m cn 90.12 91.42 81.38 79.85 89.18 93.49 81.10 84.77 86.41
7:GoogleLeNet 79.65 90.67 72.43 74.51 88.27 80.46 75.60 84.08 80.70
8:VGG-VD16 87.45 85.33 86.38 79.65 92.47 89.80 95.26 92.38 88.59
9:VGG-VD19 83.49 82.67 83.88 87.71 92.47 83.98 94.46 85.59 86.78
10:AlexNet 91.40 87.33 75.65 89.32 87.71 83.03 84.22 79.24 84.73
11:AlexNet m cn 89.42 84.67 78.88 83.78 89.36 83.55 81.10 78.32 83.63
87.41 87.70 80.88 84.50 88.54 86.07 86.17 84.06 85.67
12:BSAG-LFD 86.27 86.87 84.60 82.87 70.20 80.63 78.78 71.39 80.20
13:Blob SC 77.67 83.33 82.10 75.22 59.28 78.83 66.13 59.83 72.79
14:Shearlet-Weibull 73.72 76.67 79.60 86.80 81.30 69.91 72.38 83.63 78.00
15:GWT-Weibull 79.75 78.67 70.25 84.28 81.30 74.54 77.17 83.39 78.66
16:LCVP 76.60 66.00 47.75 77.12 77.45 79.00 70.01 69.56 70.43
17:MB-LBP 78.26 80.67 81.38 83.37 69.29 70.60 77.22 78.32 77.38
78.71 78.70 74.28 81.61 73.13 75.58 73.61 74.35 76.24
融合5/8 88.84 85.33 83.88 92.14 93.12 90.49 96.88 94.00 90.58
融合5/12 92.79 92.67 88.88 96.98 87.71 90.49 88.26 90.53 91.03
融合5/8/12 95.94 90.00 88.88 92.14 92.30 91.43 97.63 97.46 93.22
融合5/8/14 91.51 88.67 87.10 93.75 94.68 91.43 98.44 95.85 92.67
融合5/8/15 90.91 90.00 88.88 92.14 93.94 89.80 96.88 95.61 92.27
融合5/8/12/14 93.38 88.00 91.38 93.75 93.49 92.12 97.63 94.92 93.08
融合5/8/12/17 93.38 90.00 91.38 93.75 92.75 92.12 97.63 97.46 93.55
CNN-05 - - - - - - 91.00 - - - - - - 89.00 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
CNN-05 +支持向量机 - - - - - - 83.00 - - - - - - 72.55 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -