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A Two-Dimensional Spectral Inversion Algorithm for Low-field NMR

A low-field nuclear magnetic resonance and inversion algorithm technology, which is applied in magnetic resonance measurement, measurement using NMR imaging system, and magnetic variable measurement, etc., to achieve high calculation accuracy, stable inversion results, and simplified inversion process.

Active Publication Date: 2018-10-12
UNIV OF SHANGHAI FOR SCI & TECH
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Problems solved by technology

The key to these regularization algorithms is how to choose an appropriate regularization factor. The selection algorithm of the existing regularization factor requires some human intervention and needs to be improved.

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  • A Two-Dimensional Spectral Inversion Algorithm for Low-field NMR
  • A Two-Dimensional Spectral Inversion Algorithm for Low-field NMR
  • A Two-Dimensional Spectral Inversion Algorithm for Low-field NMR

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Embodiment Construction

[0028] The specific embodiments provided by the present invention will be described in detail below in conjunction with the accompanying drawings.

[0029] as attached figure 1 As shown, a low-field NMR two-dimensional spectrum inversion algorithm based on PDCO includes the following steps:

[0030] a. Read the raw data files collected by the low-field nuclear magnetic resonance equipment.

[0031] Read the raw data files collected by the low-field nuclear magnetic resonance equipment, and extract information such as sampling time and corresponding sampling data M contained in the data files.

[0032] b. Perform preprocessing operations such as horizontal relaxation time and longitudinal relaxation time distribution on the original data, matrix splicing, tensor product, etc. to obtain the inversion core matrix K and signal amplitude m.

[0033] The two-dimensional inversion problem is to solve the Fredholm integral equation with two kernels shown in formula (1), τ 2 Indicat...

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Abstract

The invention relates to a low-field nuclear magnetic resonance (NMR) two-dimensional spectrum inversion algorithm which extends a PDCO (a primitive dual interior point method for convex objectives) to two-dimensional space for solving a two-dimensional inversion problem. Compared with other low-field NMR inversion algorithms reported in domestic and foreign literatures, the inversion algorithm of the invention uses L1 regularization and L2 regularization instead of just the L2 regularization, thereby getting closer to the sparseness of an original signal and acquiring spectral distribution that may more reflect a reality. The PDCO can ensure the non-negativity of a solution, and does not need additional nonnegative constraint calculation, which simplifies an inversion process. The inversion algorithm of the invention can also distinguish closely adjacent peaks and achieves high computational accuracy. The inversion algorithm of the invention has good robustness and may obtain stable inversion results under different SNR data.

Description

technical field [0001] The invention relates to a nuclear magnetic resonance signal processing technology, in particular to a low-field nuclear magnetic resonance two-dimensional spectrum inversion algorithm based on PDCO. Background technique [0002] Worldwide, nuclear magnetic resonance technology is developing rapidly and has been widely developed in many fields, such as the application of high-field-strength nuclear magnetic resonance technology to clinical diagnosis of the human body. With the continuous development of nuclear magnetic resonance technology, it is found that nuclear magnetic resonance technology can not only be applied clinically, but also in other fields (such as food science, agriculture, petroleum energy, material science, textile chemical industry, etc.) effect. Many scientific studies have proved that the application of nuclear magnetic resonance analysis technology in these fields can solve problems that cannot be solved by other existing scienti...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R33/56
CPCG01R33/56
Inventor 苏冠群聂生东周小龙王丽嘉张英力杨培强
Owner UNIV OF SHANGHAI FOR SCI & TECH
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