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Global probability fiber tracking method based on spherical convolution

A convolutional and global technology, applied in the fields of neuroanatomy and medical imaging, can solve the problems of inability to consider local fiber orientation distribution and low precision

Active Publication Date: 2016-10-12
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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  • Global probability fiber tracking method based on spherical convolution
  • Global probability fiber tracking method based on spherical convolution
  • Global probability 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 fODF on the unit sphere, express:

[0042] S ( g ) / S 0 = F ( x ^ ) ⊗ R ( g , x ^ ) - - - ( 1 ) ...

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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] Fiber 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 diseased populations; it has been proven that in deterministic tracking techniques, 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 research...

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Application Information

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IPC IPC(8): G06T7/00G06T7/20
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