CT image data processing method and device and storage medium

Abstract

The invention provides a CT image data processing method and device and a storage medium. The method includes: acquiring multiple CT images each including a group of layer images of a human body part;selecting a preset number of layer images arranged at intervals from the layer images of the CT images as training images of the CT images, and synthesizing the training images; inputting the synthesized image into multiple pre-established network models separately for training; fusing the respective trained network models to obtain a fused network model; training the fused network model; inputting the target CT image into the trained fused network model, and outputting a pathological prediction result of the target CT image. The method selects multiple training images from different positions in the respective CT images, synthesizes the training images to obtain a synthesized image, trains the basic network models by the synthesized image, improves the accuracy of network training, and integrates the trained network models to obtain a fused network models, thereby improving robustness and prediction accuracy.

Description

technical field [0001] The present invention mainly relates to the technical field of image processing, in particular to a CT image data processing method, device and storage medium. Background technique [0002] The original format of the image data obtained by CT tomography is a DCM file. A DCM file is a file that follows the DICOM (DICOM: Digital Imaging and Communications in Medicine, medical digital image transmission protocol) standard, and is widely used in the medical industry. CT images are layered images, commonly used as cross-sections, and often contain multiple continuous layered images in order to display the entire organ. At present, the image processing network model is mainly used to analyze and process CT images, and the image is preprocessed before the analysis and processing. During the preprocessing process, image features are likely to be lost, and the output analysis data is not accurate enough. Contents of the invention [0003] The technical prob...

AI Technical Summary

Problems solved by technology

At present, the image processing network model is mainly used to analyze and process CT images, and the images are preprocessed before analysis and processing. During the preprocessing process, image features are likely to be lost, and the output analysis data is not accurate enough.

Images