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A Global Probabilistic Fiber Tracking Method Based on Spherical Convolution

A convolution and fiber technology, applied in the fields of medical imaging and neuroanatomy, it can solve the problems of low precision and inability to consider the local fiber orientation distribution, etc., and achieve the effect of high precision

Active Publication Date: 2018-10-23
樾脑云符医学信息科技(浙江)有限公司
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Problems solved by technology

[0003] In order to overcome the shortcomings of the existing fiber tracking methods that cannot consider the local fiber orientation distribution and have low precision, the present invention provides a global probabilistic fiber tracking method based on spherical convolution that effectively considers the local fiber orientation distribution and has high precision.

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  • A Global Probabilistic Fiber Tracking Method Based on Spherical Convolution
  • A Global Probabilistic Fiber Tracking Method Based on Spherical Convolution
  • A Global Probabilistic Fiber Tracking Method Based on Spherical Convolution

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Embodiment Construction

[0038] The present invention will be further described below.

[0039] A global probabilistic fiber tracking method based on spherical convolution, comprising the following steps:

[0040] 1) Diffusion model estimation

[0041] Estimate spherical convolution SD, S(g) / S by solving a linear system and recycling a spherical Gaussian kernel problem 0 and N gradient directions g can be approximated by the convolution of the response function and the fiber orientation distribution function on the unit sphere, express:

[0042]

[0043] in, is the sample convolution direction, and the response function is defined as:

[0044]

[0045] δ is the product of diffusion time and diffusion coefficient, so by S(g) / S 0 and Obtain the fiber orientation distribution fiber direction distribution function, Estimated by minimizing the following energies:

[0046]

[0047] Represented as a linear system by the non-negative least squares method; is the jth fiber orientation ...

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Abstract

The invention provides a global probability fiber tracking method based on spherical convolution. The method comprises the steps that fiber orientation distribution on a unit sphere is calculated through the convolution of a diffusion signal and a response function; the original fiber orientation distribution fODF is replaced by a spherical Gaussian kernel method to acquire a group of new fODF; global probability fiber tracking based on a group tracking algorithm is carried out to acquire prior probability and observation density, and then posterior distribution is calculated; on the basis of the posterior distribution, the sum and average of global fiber functions are calculated; a tracking start point is established to start tracking; and a relatively accurate fiber structure is acquired by choosing the best direction. The global probability fiber tracking method based on spherical convolution effectively considers local fiber orientation distribution and has high precision.

Description

technical field [0001] The invention relates to the fields of medical imaging and neuroanatomy under computer graphics, in particular to a fiber tracking method. Background technique [0002] Tractography based on magnetic resonance diffusion-weighted shaping is the only tool to obtain information on neural structure and anatomical connectivity; it estimates possible fiber paths by tracking the main diffusion directions of local tensor orientations; fiber paths represent the human brain in the form of a complex network diagram and through it to investigate neurologic pathologies and sick populations; it has been proven that in deterministic tracking techniques, the fiber paths are always diverse and cannot be affected by noise, splitting, head motion and image artifacts Uncertainties in reconstructing trajectories; to overcome these limitations, tractography methods were developed to quantify and visualize uncertainties related to fiber paths; in recent years researchers hav...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T7/207G06T7/269
CPCG06T7/0012G06T2207/10088G06T2207/30016
Inventor 冯远静何建忠吴烨张军徐田田周思琪黄奕奇
Owner 樾脑云符医学信息科技(浙江)有限公司