Image semantic segmentation method and system based on dense feature reverse fusion

The invention discloses an image semantic segmentation method and system based on dense feature reverse fusion, and the method comprises the steps: carrying out the image preprocessing of a to-be-detected medical image, and obtaining a preprocessed image; inputting the preprocessed image into a feature encoder for encoding processing to obtain an image with rough features; and inputting the image with the rough features into a dense feature reverse fusion decoder for decoding processing to obtain an image semantic segmentation result. The module comprises a preprocessing module, an encoding module and a decoding module. By using the method, the feature expression capability of the dense feature reverse fusion network and the accuracy of a semantic segmentation output result can be improved. The image semantic segmentation method and system based on dense feature reverse fusion can be widely applied to the technical field of semantic segmentation image processing. 本发明公开了一种基于密集特征反向融合的图像语义分割方法及系统，该方法包括：对待检测的医学图像