Tencent Technology (Shenzhen) Company Limited

Tencent Technology Company Limited

Shuang Yu

Yefeng Zheng

Kai Ma

Wenting Chen

Wei Ji

An image segmentation method includes: encoding an original image containing a target object based on a prior knowledge vector, to obtain a target feature map, the prior knowledge vector comprising a plurality of prior knowledge weights each representing accuracy of a corresponding rater labeling a region of an object in an image; decoding the target feature map, to obtain a first segmented image of the original image, the first segmented image indicating a target region in which the target object is located in the original image; performing image reconstruction on the first segmented image based on the prior knowledge vector, to obtain labeled segmented images, wherein one labeled segmented image corresponds to one prior knowledge weight and indicates a target region labeled by a corresponding rater; and processing the target feature map based on the labeled segmented images, to obtain a second segmented image of the original image.

Image segmentation method and apparatus, computer device, and storage medium

This present disclosure relates to the technical field of artificial intelligence, and provides a vessel image classification method and apparatus, a device, and a storage medium. The method includes: inputting a first vessel image sample into a first image processing model, and obtaining a predicted enhanced image and predicted vessel location information; and training the first image processing model based on a second vessel image sample, vessel location labeling information, the predicted enhanced image, and the predicted vessel location information. In the above solution, the impact of image quality on the vessel classification is considered during training of the vessel classification model, so that an end-to-end vessel classification model subsequently generated based on the trained first image processing model can realize a higher classification accuracy for a low quality vessel image, thereby improving the accuracy of classifying vessels in the vessel image by artificial intelligence.

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Shenzhen, China

Shuang Yu