Cervical squamous intraepithelial lesion recognition algorithm based on deep learning

The invention discloses a cervical squamous intraepithelial lesion recognition algorithm based on deep learning. The cervical squamous intraepithelial lesion recognition algorithm comprises the following steps: acquiring a prepared cervical digital pathological image; performing cell nucleus segmentation on the pathological image by using a VGG16 improved U-net algorithm to obtain a Mask image ofthe cell nucleus; performing region segmentation on the pathological image by adopting a superpixel clustering algorithm, calculating a density matrix by combining the Mask image, and extracting density features to obtain a density image; and combining the three data sets of the pathological image, the Mask image and the density image, and performing identification by using an integrated CNN. Thealgorithm has the advantages that cell nucleus segmentation and pathological image recognition based on cell nucleus density features are achieved, a simple CNN model is higher in efficiency, resources are saved, and meanwhile