A method and system for intelligent detection of fetal corpus callosum with multimodal imaging

Abstract

The present invention proposes a multimodal image fetal corpus callosum intelligent detection method and system. The detection method includes: marking the corpus callosum target frame and image modality-section information labeling on the multimodal section medical image to form the corpus callosum target detection Data set; preprocess the multimodal section medical images in the corpus callosum target detection dataset, encode the modality-section information of the multimodal section medical images; establish the fetal corpus callosum intelligence including feature extraction network model and Transformer network model Detection model; train the fetal corpus callosum intelligent detection model to obtain the trained fetal corpus callosum intelligent detection model; use the trained fetal corpus callosum intelligent detection model to perform fetal corpus callosum intelligent detection on the multi-modal section medical images to be detected, and obtain fetal corpus callosum detection result. The present invention utilizes a feature extraction network model and a Transformer network model to realize accurate positioning of fetal corpus callosum in multimodal images.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a method and system for intelligent detection of fetal corpus callosum in multimodal images. Background technique [0002] At present, the location of the fetal corpus callosum mainly depends on the judgment of the doctor. This method relies heavily on the doctor's experience and requires a large amount of work. It can be seen that how to achieve accurate positioning of the fetal corpus callosum in multimodal images has become an urgent technical problem to be solved. SUMMARY OF THE INVENTION [0003] The purpose of the present invention is to provide an intelligent detection method and system of the fetal corpus callosum in a multi-modal image, so as to realize the accurate positioning of the fetal corpus callosum in the multi-modal image. [0004] For achieving the above object, the present invention provides the following scheme: [0005] A multimodal imaging fet...

AI Technical Summary

Problems solved by technology

[0002] At present, the positioning of the fetal corpus callosum mainly depends on the judgment of doctors. This method relies heavily on the experience of doctors, and the workload is relatively large.

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