Accurate Detection of Chylous Blood Levels by Deep Learning

Abstract

Chylous blood, a kind of abnormal blood with an increasing proportion, should be excluded from unpaid blood donation. Therefore, it is important to determine the level of chylous blood, to judge that whether blood is applicable. In this manuscript, the image was preprocessed by the image acquisition device of the background board. Moreover, an improved ResNet-50 neural network model of chylous blood level based on images was established which decreased the parameters by about 44.5%, and thus greatly reducing the amount of calculation and improving the ability of the network to distinguish image details. It was found that the average values of precision, sensitivity, and F1-Score of the model were all above 0.95. Furthermore, the accuracy of the 5-level determination of the plasma chylous blood level was above 0.95. Compared with manual judgment, this method significantly improved the efficiency and accuracy of detection.

Keywords

• Chylous blood
• ResNet
• deep learning
• image processing