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System and method for predicting truncated image, method for preparing data, and medium therefor

An image data and image technology, applied in image data processing, 2D image generation, image enhancement, etc., can solve the problems of single data type, learning, and inability to input original image data, and achieve the effect of accurate acquisition and accurate prediction of results.

Pending Publication Date: 2020-07-03
GENERAL ELECTRIC CO
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Problems solved by technology

Hospitals or research institutions and departments continue to accumulate raw image data every day, but we obviously cannot simply input these accumulated raw image data into the AI ​​network for learning, because the performance of AI depends on the quality of the input data, not quantity
On the other hand, to predict a truncated image through AI, it is necessary to have an input data set corresponding to a distorted image and a fine standard data set corresponding to a fine standard image without data truncation to be input into the AI ​​​​network at the same time, but such an image is not easy. Get, or, the data type is relatively simple

Method used

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  • System and method for predicting truncated image, method for preparing data, and medium therefor
  • System and method for predicting truncated image, method for preparing data, and medium therefor
  • System and method for predicting truncated image, method for preparing data, and medium therefor

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no. 1 example

[0043] refer to figure 2 , in the first embodiment according to the present invention, the above step 200 may further include the following sub-steps 210 to 216.

[0044] Specifically, in sub-step 210, the original image without data truncation is received. The original image is usually a slice image, but sometimes a projected image may also be provided. However, even if a projected image is provided, it can be converted into a sliced ​​image by back-projection processing.

[0045] refer to image 3 , in sub-step 212, virtual translation (offset) of the part (gray white part) corresponding to the target object in the original image to partially move out of the scanning domain, so as to obtain a virtual refined standard image. It should be noted that, in this process, the original slice image itself remains unchanged. The scanning field itself is a circle centered at the focal point, which can be expressed as DFOV50, for example, where "50" is the diameter of the scanning ...

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Abstract

The invention relates to a system and method for predicting a truncated image, a method for preparing data, and a medium therefor. The method for preparing the data comprises a virtual simulation stepused for carrying out virtual simulation on image data so as to obtain a virtual distorted image with data truncation and a virtual fine standard image without data truncation at the same time. The method for predicting the truncated image predicts the truncated image based on the trained learning network, and the trained learning network is obtained by performing data training based on a data set composed of the virtual distorted image and the virtual fine standard image which are obtained through the method for preparing the data. Also provided are a system corresponding to the method and arecording medium in which the recorded instruction can implement the method.

Description

technical field [0001] The present invention relates to the field of medical imaging, in particular to a technique for preparing data for predicting a truncated image and predicting a truncated image based on the data in computed tomography (CT) imaging. Background technique [0002] During the CT scanning process, detectors are used to collect X-ray data passing through the patient's body, and then the collected X-ray data are processed to obtain projection data. Slice images can be reconstructed from these projection data. Complete projection data allows reconstruction of accurate slice images for diagnosis. [0003] However, if the patient is large or placed in a special posture, some parts of the patient's body will be out of the scan domain, and the detector will not be able to collect complete projection data. This is called data truncation. This data truncation introduces truncation artifacts and ultimately leads to distorted reconstructed images. Distorted images ...

Claims

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Application Information

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IPC IPC(8): G06T11/00
CPCG06T11/005G06T2207/10081G06T2207/20081
Inventor 赵冰洁王学礼孙妍
Owner GENERAL ELECTRIC CO
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