Abstract: Provided are a cell counting method and apparatus, a device, a storage medium, and a program product, relating to the technical field of image processing. The method includes: acquiring a cell image and cell labeling information in one-to-one correspondence with the cell image; inputting the cell image into a pre-constructed cell prediction model to obtain predicted cell point information corresponding to the cell image, where the predicted cell point information includes predicted cell point position information and confidence values in one-to-one correspondence with predicted cell points; performing one-to-one matching on reference points corresponding to the cell image with the predicted cell points based on the cell labeling information and the predicted cell point information to obtain a matching result; and adjusting the cell prediction model based on the matching result, where the cell prediction model is used for predicting cell positions and cell counts.

Abstract: The present disclosure relates to a subtle cornea deformation identification method and device based on a pixel-level corneal biomechanical parameter, including the following steps: step 1, sampling and analyzing a dynamic video of corneal stress deformation in a historical database, and calculating pixel-level data; and step 2, configuring an ensemble classifier based on a sampling result and detecting a local change in corneal biomechanics, thus identifying a subtle cornea deformation. The present disclosure has high measurement accuracy and is capable of detecting a local subtle biomechanical change.

Abstract: The present disclosure relates to a subtle cornea deformation identification method and device based on a pixel-level corneal biomechanical parameter, including the following steps: step 1, sampling and analyzing a dynamic video of corneal stress deformation in a historical database, and calculating pixel-level data; and step 2, configuring an ensemble classifier based on a sampling result and detecting a local change in corneal biomechanics, thus identifying a subtle cornea deformation. The present disclosure has high measurement accuracy and is capable of detecting a local subtle biomechanical change.