Convolutional neural network-based segmentation network applied to image recognition of angiodysplasias lesion under capsule endoscopy

Table 1 Details of the training set data and test set data

Lesion type	Lesion morphology	Number of pictures/pieces
		Training set	Test set
Telangiectasia	Red cluster	838	38
	Red spider nevus	162	4
Venous dilatation	Red branched	752	38
	Blue branched	2583	1088
Vein tumor	Blue cluster	3058	332

Table 2 Comparison of model accuracy

Network type	PPV (%)	NPV (%)	mIOU	PA (%)	Parameter (M)	Float calculation amount (G)	Time (s)
PSPNet	85.14	98.62	0.64	98	51.43	829.10	0.9
DeeplabV3+	45.07	99.75	0.59	89	59.34	397.00	0.95
UperNet	92.55	95.69	0.69	98	126.08	34.94	0.9
Our model	94.27	98.74	0.69	99	46.38	467.2	0.6

PPV: Positive predictive value; NPV: Negative predictive value; mIOU: Mean intersection over union; PA: Pixel accuracy.