Peripheral Blood Leukocyte Classification CNN Model for Dogs and Cats by ResNet

Abstract

We examine the usefulness of an AI-based peripheral blood leukocyte classification and screening technique based on microscopic blood images of cats and dogs. Peripheral blood smears of MG-stained cats and dogs were used as the target samples, and the accuracy of leukocyte image classification was inferentially evaluated using a CNN model obtained by learning with leukocyte images. The inferential evaluation after transfer learning was 0.10 for Eosinophil, 0.80 for Lymphocyte, 0.80 for Monocyte, and 0.7 for Neutrophil. However, more training images are needed to use this technique in the field.