BLOOD SMEAR FULL-VIEW INTELLIGENT ANALYSIS METHOD, AND BLOOD CELL SEGMENTATION MODEL AND RECOGNITION MODEL CONSTRUCTION METHOD

A blood smear full-view intelligent analysis method, and a blood cell segmentation model and recognition model construction method. The analysis method comprises: collecting a plurality of original blood smear single-view images, establishing an original blood smear single-view image group, and establishing a blood smear full-view image on the basis of the plurality of original blood smear single-view images; constructing an image restoration model on the basis of a first training set and a first verification set; constructing an image segmentation model on the basis of a second training set and a second verification set, obtaining a third training set and a third verification set on the basis of a plurality of segmented individual blood cell images, and constructing an image recognition model; and finally obtaining a blood cell classification result. According to the method, full-view blood cells are analyzed on the basis of an artificial intelligence algorithm, thereby greatly reducing interference of human factors, improving objectivity of an inspection result, and improving blood cell analysis and classification accuracy; recognition and analysis can be realized for picture input meeting requirements, the algorithm robustness and accuracy are higher than those of conventional image recognition algorithms, and the overall time is greatly shortened.