Medical image cross-modal synthesis system and method based on multi-source confrontation strategy

A confrontation strategy and medical imaging technology, applied in the direction of neural learning methods, character and pattern recognition, biological neural network models, etc., can solve the problems of limited physiological characteristic information of subjects, high cost, and difficult to meet the needs of use
CN114387481APending Publication Date: 2022-04-22E SURFING IOT CO LTD
0 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
E SURFING IOT CO LTD
Publication Date
2022-04-22

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses a medical image cross-modal synthesis system and a medical image cross-modal synthesis method based on a multi-source adversarial strategy, which can accurately describe key features of a target domain modal image and improve the quality of synthesizing the target domain modal image, thereby obtaining the target domain modal image better meeting actual requirements. The system comprises a multi-source input fusion network unit which is provided with a first convolution layer and a feature cascade layer; the generation neural network unit comprises a coding compression sub-network and a decoding expansion sub-network; the identification neural network unit is provided with a fourth convolutional layer and a second down-sampling layer, extracts a first advanced feature map of the first target domain modal image and a second advanced feature map of the real modal image, and identifies the first advanced feature map and the second advanced feature map; the difference between the actual recognition value and the expected recognition value is obtained and fed back to the neural network generation unit; and outputting the second target domain modal image when the difference is smaller than the threshold value.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The present invention relates to the field of big data / AI technology, in particular to a medical image cross-modal synthesis system and method based on a multi-source confrontation strategy. Background technique

[0002] At present, medical imaging includes many imaging modalities, such as X-ray, computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET) and so on. Different imaging modalities can provide multi-level information for clinical diagnosis from different angles, thereby significantly reducing the rate of misdiagnosis and missed diagnosis. However, in the actual clinical diagnosis process, due to factors such as high cost and radiation hazards, the image data of some modalities is relatively scarce. In related technologies, cross-modal synthesis of medical images is an effective solution to provide missing modal data, but the current single-source domain modal images can provide limited physiological char...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More