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Multi-modal medical image method based on deep learning

A technology of medical imaging and deep learning, applied in the field of multi-modal medical imaging based on deep learning, can solve problems such as low diagnostic efficiency and heavy workload, and achieve the effect of improving work efficiency, improving accuracy, and improving accuracy

Inactive Publication Date: 2019-05-21
SHAANXI UNIV OF CHINESE MEDICINE
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Problems solved by technology

Due to the tens of thousands of medical images in the hospital every day, the workload is huge and the diagnostic efficiency is low

Method used

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  • Multi-modal medical image method based on deep learning
  • Multi-modal medical image method based on deep learning
  • Multi-modal medical image method based on deep learning

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Embodiment Construction

[0029] In order to make the objects and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0030] like figure 1 As shown, the embodiment of the present invention provides a method for multimodal medical imaging based on deep learning, including the following steps:

[0031] S1. Using computerized tomography and magnetic resonance imaging equipment to obtain medical images of the parts of the patient to be detected;

[0032] S2. Generate a grayscale image according to the pixel edge intensities of the two medical images obtained in step S1, and perform sharpening processing on the obtained medical image based on the grayscale image, and obtain a gradient image of the obtained image; the grayscale The grayscale of each pixel in the fi...

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Abstract

The invention discloses a multi-modal medical image method based on deep learning. The method comprises: utilizing a deep learning algorithm to simultaneously carry out tomography on the electronic computer; performing feature extraction on the magnetic resonance image; secondly, the gradient image of the image is corrected through the foreground mark obtained through distance transformation and the background mark obtained through watershed transformation, then the features extracted by the deep learning model are subjected to score level fusion through a fusion algorithm, the accuracy of similarity calculation between the images is improved, and therefore the accuracy of a follow-up diagnosis result is improved; and finally, the fused image score is used for realizing automatic output ofa diagnosis result based on the BP neural network model, so that the working efficiency of medical personnel is greatly improved.

Description

technical field [0001] The invention relates to the technical field of multimodal medical imaging, in particular to a method for multimodal medical imaging based on deep learning. Background technique [0002] At present, with the advent of precision medicine and the era of big data, in addition to diagnostic text information, the analysis and application of image data has become one of the more core links in clinical medicine. [0003] Medical imaging refers to the technology and processing process of obtaining internal tissue images of the human body or a certain part of the human body in a non-invasive manner for medical treatment or medical research. It includes the following two relatively independent research directions: medical imaging system and medical image processing. The former refers to the process of image formation, including the research on imaging mechanism, imaging equipment, imaging system analysis and other issues; the latter refers to the further proces...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/136
Inventor 郑运松牛锐王咪
Owner SHAANXI UNIV OF CHINESE MEDICINE
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