| CPC G06T 7/10 (2017.01) [G06F 18/25 (2023.01); G06N 3/045 (2023.01); G06N 3/084 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20221 (2013.01); G06T 2207/30016 (2013.01)] | 17 Claims |
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1. A method for reconstructing a dendritic tissue in an image performed by a computer device, the method comprising:
acquiring original image data corresponding to a target image of a target dendritic tissue and reconstruction reference data corresponding to the target image, the reconstruction reference data being determined based on a local reconstruction result of the target dendritic tissue in the target image;
applying a target segmentation model to the original image data and the reconstruction reference data to acquire a target segmentation result corresponding to the target image, the target segmentation result being used for indicating a target category of each pixel in the target image, and the target category of any pixel being used for indicating that the pixel belongs to the target dendritic tissue or that the pixel does not belong to the target dendritic tissue, wherein the target segmentation model is trained by: acquiring original sample image data respectively corresponding to at least one sample image, reconstruction reference sample data respectively corresponding to the at least one sample image, and standard segmentation results respectively corresponding to the at least one sample image; and performing supervised training on an initial segmentation model based on the original sample image data respectively corresponding to the at least one sample image, the reconstruction reference sample data respectively corresponding to the at least one sample image, and the standard segmentation results respectively corresponding to the at least one sample image to obtain the target segmentation model; and
reconstructing the target dendritic tissue in the target image based on the target segmentation result to obtain a complete reconstruction result of the target dendritic tissue in the target image.
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7. A computer device, comprising a processor and a memory, the memory storing at least one program code, the at least one program code being loaded and executed by the processor and causing the computer device to implement a method for reconstructing a dendritic tissue in an image, the method including:
acquiring original image data corresponding to a target image of a target dendritic tissue, and reconstruction reference data corresponding to the target image, the reconstruction reference data being determined based on a local reconstruction result of the target dendritic tissue in the target image;
applying a target segmentation model to the original image data and the reconstruction reference data to acquire a target segmentation result corresponding to the target image, the target segmentation result being used for indicating a target category of each pixel in the target image, and the target category of any pixel being used for indicating that the pixel belongs to the target dendritic tissue or that the pixel does not belong to the target dendritic tissue, wherein the target segmentation model is trained by: acquiring original sample image data respectively corresponding to at least one sample image, reconstruction reference sample data respectively corresponding to the at least one sample image, and standard segmentation results respectively corresponding to the at least one sample image: and performing supervised training on an initial segmentation model based on the original sample image data respectively corresponding to the at least one sample image, the reconstruction reference sample data respectively corresponding to the at least one sample image, and the standard segmentation results respectively corresponding to the at least one sample image to obtain the target segmentation model; and
reconstructing the target dendritic tissue in the target image based on the target segmentation result to obtain a complete reconstruction result of the target dendritic tissue in the target image.
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13. A non-transitory computer-readable storage medium, storing at least one program code, the at least one program code being loaded and executed by a processor of a computer device and causing the computer device to implement a method for reconstructing a dendritic tissue in an image, the method including:
acquiring original image data corresponding to a target image of a target dendritic tissue, and reconstruction reference data corresponding to the target image, the reconstruction reference data being determined based on a local reconstruction result of the target dendritic tissue in the target image;
applying a target segmentation model to the original image data and the reconstruction reference data to acquire a target segmentation result corresponding to the target image, the target segmentation result being used for indicating a target category of each pixel in the target image, and the target category of any pixel being used for indicating that the pixel belongs to the target dendritic tissue or that the pixel does not belong to the target dendritic tissue, wherein the target segmentation model is trained by: acquiring original sample image data respectively corresponding to at least one sample image, reconstruction reference sample data respectively corresponding to the at least one sample image, and standard segmentation results respectively corresponding to the at least one sample image: and performing supervised training on an initial segmentation model based on the original sample image data respectively corresponding to the at least one sample image, the reconstruction reference sample data respectively corresponding to the at least one sample image, and the standard segmentation results respectively corresponding to the at least one sample image to obtain the target segmentation model; and
reconstructing the target dendritic tissue in the target image based on the target segmentation result to obtain a complete reconstruction result of the target dendritic tissue in the target image.
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