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Model training method and device, image processing method and device and medium

A model training and image technology, applied in the computer field, can solve the problems of low utilization rate of information, inaccessible to human eyes, difficult classification and judgment, etc., and achieve the effect of accurate classification and judgment.

Active Publication Date: 2020-06-09
ZHENGZHOU UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] For a long time, the utilization rate of information contained in PET images is not high, and the human eye cannot obtain and quantify effective information from PET images
Moreover, it has always been a difficult problem to classify and judge the pathological tissue information of tumors only through image analysis before surgery.

Method used

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  • Model training method and device, image processing method and device and medium
  • Model training method and device, image processing method and device and medium
  • Model training method and device, image processing method and device and medium

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Embodiment Construction

[0024] Specific embodiments of the present disclosure will be described in detail below, and it should be noted that the embodiments described here are only for illustration, and are not intended to limit the embodiments of the present disclosure. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It will be apparent, however, to one of ordinary skill in the art that these specific details need not be employed to practice the disclosed embodiments. In other instances, well-known structures, materials or methods have not been described in detail to avoid obscuring embodiments of the present disclosure.

[0025] Throughout this specification, reference to "one embodiment," "an embodiment," "an example," or "an example" means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in the present disclosure...

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Abstract

The invention provides a model training method which comprises the following steps: acquiring a plurality of sample images, any sample image in the plurality of sample images comprising a three-dimensional PET image about a specified tumor with a known genotype; and obtaining genotype information of any sample image; determining a set of features of any sample image; training an initial model based on the obtained genotype information and the feature set of each of the plurality of sample images to obtain a target model, with the target model being used for determining genotype information about a three-dimensional PET image of a specified tumor with an unknown genotype. The invention further provides model training equipment, an image processing method and equipment and a storage medium.

Description

technical field [0001] The present disclosure relates to the field of computer technology, in particular to a model training method and device, an image processing method and device, and a storage medium. Background technique [0002] Positron Emission Tomography (PET) is an imaging technique used in nuclear medicine clinical examinations. PET technology is currently the only technology that uses anatomical morphology to perform functional, metabolic and receptor imaging. It is non-invasive and can provide three-dimensional and functional images of the whole body, which can be referred to as PET images for short. [0003] For a long time, the utilization rate of information contained in PET images is not high, and human eyes cannot obtain and quantify effective information from PET images. Moreover, it has always been a difficult problem to classify and judge the pathological tissue information of tumors only through image analysis before surgery. Only relying on people's ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/32G06K9/62
CPCG06T7/0012G06T2207/10104G06T2207/20064G06T2207/20081G06T2207/20084G06T2207/30016G06T2207/30096G06V10/25G06F18/241G06F18/24323Y02A90/10
Inventor 林予松李龙飞尚冲刘振宇赵国桦刘琦
Owner ZHENGZHOU UNIV