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Near-infrared spectrum tomography reconstruction method based on convolutional neural network

A convolutional neural network and near-infrared spectroscopy technology, applied in the field of medical image processing, can solve the problems of morbidity of tomography, limited number of measurements, and mixed noise.

Inactive Publication Date: 2019-06-25
BEIJING UNIV OF TECH
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Problems solved by technology

In the wavelength band of near-infrared light imaging, the scattering of light is much greater than the absorption, and the boundary measurement data will inevitably be mixed with noise, resulting in serious pathological problems in tomographic imaging.
In addition, due to the limited number of measurements, the problem of reconstructing the internal optical parameters of the tissue is an ill-posed problem.
However, the traditional regularization method is susceptible to artifacts caused by noise, and the imaging reconstruction time is relatively long. Therefore, the present invention considers the use of convolutional neural networks for near-infrared spectrum image reconstruction

Method used

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  • Near-infrared spectrum tomography reconstruction method based on convolutional neural network
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[0039] The present invention will be described below based on specific implementation examples and accompanying drawings.

[0040] First, a circular phantom with a diameter of 80mm is established through the toolbox nirfast of Matlab and the finite element meshing of the phantom is completed. The result of the finite element meshing is as follows figure 2 shown. In the experiment, there are 16 light sources and detectors, such as image 3 As shown, it is evenly placed on the surface of the phantom, and 240 boundary measurements can be measured for each phantom sample, and the imaging pixels are 2001 uniform finite element nodes on the circle. In order to train the network, the absorption coefficient values ​​on 2001 nodes are mapped to a 98*98 matrix to form an absorption coefficient distribution image, so the measured value is used as the input of the convolutional neural network, and the absorption coefficient distribution image is used as the input of the convolutional neur...

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Abstract

The invention discloses a near-infrared spectrum tomography reconstruction method based on a convolutional neural network, which belongs to the field of medical image processing. The convolutional neural network is used to express a nonlinear mapping relationship between the boundary measurement values of a near-infrared spectrum tomographic target and the internal optical parameter distribution,through the network training, an absorption coefficient distribution image can be obtained from the measured values, and the direct reconstruction from a sensor domain to an image domain is realized.The method can have higher calculation efficiency while ensuring accurate reconstruction of the optical parameter distribution.

Description

technical field [0001] The invention belongs to the field of medical image processing, and relates to a near-infrared spectral tomographic reconstruction method based on a convolutional neural network. Background technique [0002] Near-infrared spectroscopy (NIRS) tomography is an emerging functional medical imaging method. Its imaging device is placed around or on the surface of biological tissue without exogenous probes and will not cause damage to the tissue. In addition, the near-infrared light wave used in imaging has no damage to human tissues, so this technology is non-destructive; near-infrared light imaging can effectively perform structural and functional imaging of biological tissues, and can study the morphological structure, physiological characteristics, and pathology of biological tissues Features, metabolic functions, etc., are especially suitable for characterizing soft tissue lesions such as breast cancer and early detection of cancer. In addition, this te...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00
Inventor 冯金超孙秋婉贾克斌李哲孙中华
Owner BEIJING UNIV OF TECH