DCM myocardial diagnosis and treatment radiation image segmentation method based on a multi-scale feature pyramid

Abstract

The invention belongs to the technical field of medical image processing, and discloses a DCM myocardial diagnosis and treatment radiation image segmentation method based on a multi-scale characteristic pyramid, which is used for segmenting a cardiac MRI image and completely segmenting medical anatomical structures such as myocardium and a blood pool. According to the method, traditional convolution is replaced by convolution with holes, so that the method has the advantages that the receptive field of the convolution kernel is larger, and larger context information can be obtained; By using spatial pyramid pooling, information extraction can be carried out on the image on different scales to cope with multi-scale characteristics of the image, and even a very small object can be effectively captured; Detail information can be recovered by using an encoder structure and a decoder structure, shallow features and high-level features are fused, and a segmentation mask with rich semantics and complete details is obtained; According to the method, the workload of doctors is reduced, and the method has great significance for disease analysis and subsequent treatment plans and postoperative evaluation.

Description

technical field [0001] The invention belongs to the technical field of medical image processing, and in particular relates to a method for segmenting radiographic images of DCM myocardial diagnosis and treatment based on a multi-scale feature pyramid. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: [0003] Semantic Image Segmentation of images is an important research topic in the field of artificial intelligence and computer vision. The research aims to use algorithms to automatically or semi-automatically distinguish the areas where different objects are located in the image at a fine, pixel-level distinction. [0004] Image semantic segmentation is to distinguish the motorcycle from the person in the picture, and obtain the green segmentation mask of the motorcycle on the right and the red segmentation mask of the person. The research requires the algorithm to generate a segmentation mask of the same siz...

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Problems solved by technology

[0017]Aiming at the problems of the above existing methods, including the loss of detailed information, weak semantic information extraction a

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