Lipid droplet recognition based on watershed algorithm and convolutional neural network

Abstract

Unbalanced storage and utilization of lipids in the liver can easily lead to non-alcoholic fatty liver, obesity and metabolic syndrome. Therefore, it is very significant to detect and classify lipids in cell pathology pictures. In order to achieve accurate identification of lipid droplets, we improved the watershed algorithm to achieve the segmentation of lipid droplets, and classified the lipid droplets based on transfer learning through a convolutional neural network. The experiment shows that the improved watershed algorithm is used to segment the lipid droplets and has achieved good results. The convolutional neural network transfer learning has achieved a classification accuracy of about 99%.