Breast cancer image segmentation method and system based on parameter sharing and prior guidance

Abstract

This invention discloses a breast cancer image segmentation method and system based on parameter sharing and prior guidance, belonging to the field of medical image processing technology. The method includes the following steps: acquiring the image to be segmented; processing the image to be segmented using an image segmentation model to obtain a tumor segmentation map; wherein, the image segmentation model training process involves: extracting features from known noisy segmentation labels and corresponding medical images; inputting denoised features into a denoising channel for noise processing, inputting pathological features into a conditional channel for semantic information processing, and using a cross-attention mechanism to achieve parameter sharing between the denoising channel and the conditional channel; using a denoised stream to predict the added noise, and using a prior guidance strategy to identify and guide the tumor location during the prediction process, ultimately obtaining the segmented image. This invention utilizes the advantages of diffusion denoising technology combined with a prior knowledge guidance strategy to achieve more accurate and automated segmentation, improving the efficiency of breast cancer image detection and segmentation.

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