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Deep learning of electrical properties tomography

An electrical, property-based technology applied in the field of medical analysis systems

Pending Publication Date: 2022-02-22
KONINKLJIJKE PHILIPS NV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, conventional EPT suffers from transmit-receive phase issues that exist in tissue boundaries and noise amplification

Method used

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  • Deep learning of electrical properties tomography
  • Deep learning of electrical properties tomography
  • Deep learning of electrical properties tomography

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Embodiment Construction

[0072] Hereinafter, elements with like reference numerals in the figures are either similar elements or perform equivalent functions. If the function is equivalent, it will not be necessary to discuss previously discussed elements in subsequent figures.

[0073] Various structures, systems and devices are schematically depicted in the drawings for purposes of explanation only, so as not to obscure the present invention with details that are well known to those skilled in the art. Nevertheless, the accompanying drawings are included to describe and explain illustrative examples of the disclosed subject matter.

[0074] figure 1 is a schematic diagram of the medical analysis system 100 . The medical analysis system 100 includes a control system 111 configured to be connected to the scanning imaging system (or acquisition component) 101 . Control system 111 includes processor 103 , memory 107 , each capable of communicating with one or more components of medical system 100 . ...

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Abstract

The present disclosure relates to a method for determining electrical properties, EP, of a target volume (708) in an imaged subject (718). The method comprises: performing a first training (201) of a deep neural network, DNN, using a first training dataset, the first training dataset comprising training B1 field maps and corresponding first EP maps, the first training resulting in a pre-trained DNN configured for generating EP maps from B1 field maps; performing a second training (203) of the pre-trained DNN using conditional generative adversarial networks, GAN, and a second training dataset, wherein the pre-trained DNN is a generator of the conditional GAN, the second training dataset comprising measured B1 maps and second EP maps, the second training resulting in a trained DNN; receiving (205) an input B1 field map of the target volume and generating an EP map of the input B1 field map using the trained DNN.

Description

technical field [0001] The present invention relates to scanning imaging systems and in particular to medical analysis systems for determining the electrical properties (EP) of a target volume in an imaged object. Background technique [0002] Electrical property tomography (EPT) is a technique to noninvasively and quantitatively measure electrical properties of tissue in vivo by post-processing the magnitude and phase of the B1 field distribution. The relationship between EP and the complex B1 value is given by the so-called Helmholtz equation. Thus, the Helmholtz equation provides EP by taking as input the complex-valued B1 map obtained from the MRI. However, conventional EPT suffers from transmit-receive phase issues, which exist in tissue boundaries and noise amplification. Contents of the invention [0003] Various embodiments provide a medical analysis system for determining electrical properties (EP) of a target volume in an imaged object and a method and a comput...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/24
CPCA61B5/24A61B5/7267G06N3/084G06N3/088A61B5/055G06N3/047G06N3/045G16H30/40G01R33/443G06T11/005G06T11/006G06T2210/41
Inventor U·卡切尔N·汉佩尔
Owner KONINKLJIJKE PHILIPS NV