Abstract: An image processing method of an electronic device includes performing feature extraction on a compressed image to obtain a compression feature map of the compressed image; performing reconstruction on the compression feature map to obtain a reconstruction feature map of the compressed image; performing quality factor (QF) prediction on the compression feature map to obtain a QF of the compressed image; and generating a denoised compressed image having compression noise reduced or removed from the compressed image by performing denoising on the reconstruction feature map based on the QF.

Abstract: Methods, apparatus, device, and storage medium for identifying an abnormal cell in a to-be-detected sample are disclosed. The method includes obtaining, by a device, multi-layer images of a to-be-detected sample, the to-be-detected sample comprising a single cell and a cell cluster; obtaining, by the device, multi-layer image blocks of the single cell and multi-layer image blocks of the cell cluster according to the multi-layer images; obtaining, by the device, a first identification result by a first image identification network according to the multi-layer image blocks of the single cell; obtaining, by the device, a second identification result by a second image identification network according to the multi-layer image blocks of the cell cluster; and determining, by the device, whether an abnormal cell exists in the to-be-detected sample according to the first identification result and the second identification result.

Abstract: This application discloses a microscopic image processing method performed by a computer device. The method includes: extracting an instance image of a target object from a microscopic image; obtaining skeleton form information of the target object from the instance image, the skeleton form information representing a skeleton form of the target object; performing motion analysis on the target object based on the skeleton form information to obtain a plurality of eigenvalues; and determining an eigenvalue sequence comprising the plurality of eigenvalues as motion component information of the target object.

Abstract: An image display method includes: processing a first image to obtain a first feature image, the first image being an image of a local area of a smear captured by a microscope, and the local area including multiple objects to be tested; obtaining a second feature image corresponding to the first feature image, the second feature image and the first feature image having a same size; obtaining a third feature image according to an image obtained by overlaying the first feature image and the second feature image, a feature point in the third feature image indicating a possibility that one of the multiple objects is an abnormal object; obtaining a second image according to the third feature image; and displaying the second image superimposed on the first image.

Abstract: An apparatus, method and storage medium for controlling a pathologic microscope are provided. The method includes obtaining a pathological digital image from an incident optical path of the pathologic microscope; performing artificial intelligence (AI) analysis on the pathological digital image to generate AI analysis information; and controlling an augmented reality (AR) projection component to project the AI analysis information on a microscopic field of the pathologic microscope on an outgoing optical path.

Abstract: A method for microscope-based super-resolution includes acquiring a to-be-processed image and at least an auxiliary image, the to-be-processed image includes a target area, the auxiliary image includes an overlapping portion with the target area, and the to-be-processed image and the auxiliary image are both microscope images of a first resolution. The method further includes registering the to-be-processed image and the auxiliary image to obtain a registered image, and extracting one or more high-resolution features from the registered image. The one or more high-resolution features represent image features of the target area in a second resolution, and the second resolution is greater than the first resolution. The method also includes reconstructing, based on the one or more high-resolution features, a target image of the second resolution corresponding to the to-be-processed image of the first resolution.

Abstract: An image display method includes: processing a first image to obtain a first feature image, the first image being an image of a local area of a smear captured by a microscope, and the local area including multiple objects to be tested; obtaining a second feature image corresponding to the first feature image, the second feature image and the first feature image having a same size; obtaining a third feature image according to an image obtained by overlaying the first feature image and the second feature image, a feature point in the third feature image indicating a possibility that one of the multiple objects is an abnormal object; obtaining a second image according to the third feature image; and displaying the second image superimposed on the first image.

Abstract: Methods, apparatus, device, and storage medium for identifying an abnormal cell in a to-be-detected sample are disclosed. The method includes obtaining, by a device, multi-layer images of a to-be-detected sample, the to-be-detected sample comprising a single cell and a cell cluster; obtaining, by the device, multi-layer image blocks of the single cell and multi-layer image blocks of the cell cluster according to the multi-layer images; obtaining, by the device, a first identification result by a first image identification network according to the multi-layer image blocks of the single cell; obtaining, by the device, a second identification result by a second image identification network according to the multi-layer image blocks of the cell cluster; and determining, by the device, whether an abnormal cell exists in the to-be-detected sample according to the first identification result and the second identification result.

Abstract: An apparatus, method and storage medium for controlling a pathologic microscope are provided. The method includes obtaining a pathological digital image from an incident optical path of the pathologic microscope; performing artificial intelligence (AI) analysis on the pathological digital image to generate AI analysis information; and controlling an augmented reality (AR) projection component to project the AI analysis information on a microscopic field of the pathologic microscope on an outgoing optical path.