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Method for optimizing ultrasonic imaging system parameters based on deep study

An ultrasound imaging system and deep learning technology, which are applied in the field of optimizing ultrasound imaging system parameters, and can solve problems such as inability to adjust preset values.

Active Publication Date: 2019-06-04
CHISON MEDICAL TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] With the development of social technology, deep learning technology has made some progress in other fields. However, in the field of medical ultrasound, due to the complexity of the ultrasound system, deep learning technology still has some defects in the field of medical devices, and it still cannot be quickly and quickly based on the current image. , Accurate, intelligent adjustment of the current preset value and other shortcomings

Method used

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  • Method for optimizing ultrasonic imaging system parameters based on deep study
  • Method for optimizing ultrasonic imaging system parameters based on deep study
  • Method for optimizing ultrasonic imaging system parameters based on deep study

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0045] Embodiment 1; The technical solution is specifically divided into a training stage and an application stage to be executed sequentially, and the steps of each stage are as follows:

[0046] Training phase:

[0047] Step 101: Randomly select the preset value of the parameters of the ultrasound imaging system from the ultrasound equipment, and collect an ultrasound image under the condition of the preset value every time a preset value is selected, save the ultrasound image and record the acquired ultrasound image together. The preset value parameters used in the image, so as to obtain the image sample set OI (including 1000 images) and the preset value parameter sample set OP (including 1000 sets of preset value parameters);

[0048] Step 102: Obtain the optimized image sample set EI corresponding to OI (including 1000 images with the same content as each image in OI but with better quality);

[0049] Step 103: Use OI and EI to train as image 3 The shown DCGAN (deep c...

Embodiment 2

[0057] Embodiment 2: The technical solution is specifically divided into a training stage and an application stage to be executed sequentially, and the steps of each stage are as follows:

[0058] Training phase:

[0059] Step 201: Randomly select the preset value of the parameters of the ultrasound imaging system from the ultrasound equipment, and collect an ultrasound image under the condition of the preset value every time a preset value is selected, save the ultrasound image and record the acquired ultrasound image together. The preset value parameters used in the image, so as to obtain the image sample set OI (including 2000 images) and the preset value parameter sample set OP (including 2000 sets of preset value parameters);

[0060] Step 202: Obtain the optimized image sample set EI corresponding to OI (including 2000 images with the same content as each image in OI but with better quality);

[0061] Step 203: Use the OI sample set and the OP sample set to train such a...

Embodiment 3

[0067] Embodiment 3: The technical solution is specifically divided into a training stage and an application stage to be executed sequentially, and the steps of each stage are as follows:

[0068] Training phase:

[0069] Step 301: Randomly select the preset value of the parameters of the ultrasound imaging system from the ultrasound equipment, and each time a preset value is selected, an ultrasound image is collected under the condition of the preset value, the ultrasound image is saved, and the ultrasound image collected is also recorded. The preset value parameters used in the image, so as to obtain the image sample set OI (including 2000 images) and the preset value parameter sample set OP (including 2000 sets of preset value parameters);

[0070] Step 302: Obtain the optimized image sample set EI corresponding to OI (including 2000 images with the same content as each image in OI but with better quality);

[0071] Step 303: Use the preset value parameter sample set OP to...

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Abstract

The invention provides a method for optimizing ultrasonic imaging system parameters based on deep study. The method comprises the following steps of step 1, collecting samples for training the neuralnetwork, wherein the samples comprise ultrasonic image samples I and corresponding ultrasonic imaging system parameter vector samples P used by an ultrasonic imaging system when the ultrasonic image samples are collected; step 2, establishing a neural network model, and training the neural network to convergence through the samples collected in the step 1, so as to obtain a trained neural networksystem onn; and step 3, using an original ultrasonic imaging system parameter vector P or an original ultrasonic image as input, performing inputting into the trained neural network system onn obtained in the step 2, and at the time, from an onn output terminal, obtaining parameters namely optimized ultrasonic imaging system parameter vectors ep=onn(p). Through adoption of the method disclosed bythe invention, the purpose of improving the quality of ultrasonic images through the optimized ultrasonic imaging parameters can be realized.

Description

technical field [0001] The invention relates to a medical ultrasound imaging system, in particular to a method for optimizing parameters of the ultrasound imaging system. Background technique [0002] Ultrasound images are widely used in clinical practice because of their non-invasive, low price, and fast imaging. However, due to the physical characteristics of ultrasound imaging, there are many image parameters. In order to obtain a desired ultrasound image, many parameters need to be adjusted, and it is still relatively cumbersome for users to adjust. [0003] At present, most ultrasonic diagnostic equipment provide presets (Presets) to set preset values ​​for each imaging parameter. Presets are an entity collection containing all controllable imaging parameters. Commonly used imaging parameters can be roughly divided into three categories: image acquisition parameters, display parameters, and signal processing parameters. The image acquisition parameters mainly control...

Claims

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Application Information

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IPC IPC(8): A61B8/00
CPCG06N3/088A61B8/585A61B8/54G06N3/047G06N3/044G06N3/045G16H30/40A61B8/5223G06N3/08G06T7/0012G06T2207/10132G06T2207/20081G06T2207/20084
Inventor 张智伟赵明昌陆坚
Owner CHISON MEDICAL TECH CO LTD