Self-adaption data analysis method for small-animal brain functional magenetic resonance imaging

A magnetic resonance imaging and data analysis technology, applied in image analysis, image data processing, image enhancement, etc., can solve problems that are difficult to meet the needs of small animal brain functional imaging research, and achieve reduced subjectivity, high efficiency, and self-adaptation strong effect

Active Publication Date: 2018-02-13
INST OF HIGH ENERGY PHYSICS CHINESE ACADEMY OF SCI
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Problems solved by technology

[0004] Currently, the standard brain template with a single FOV, which is the most widely used in human brain functio

Method used

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  • Self-adaption data analysis method for small-animal brain functional magenetic resonance imaging
  • Self-adaption data analysis method for small-animal brain functional magenetic resonance imaging

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Embodiment Construction

[0033] The present application will be further described in detail below in conjunction with the examples. It can be understood that the specific embodiments described here are only used to explain related inventions, rather than to limit the invention.

[0034] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below in conjunction with embodiments.

[0035] The adaptive small animal brain functional magnetic resonance imaging data analysis method provided by the embodiment of the present invention comprises the following steps:

[0036] S100: Acquire the whole-brain scan images of each tested animal multiple times, and perform time slice correction on each said whole-brain scan image of each said tested animal, so as to eliminate the time of each scan layer in the data acquisition cycle deviation;

[0037] Th...

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Abstract

The invention discloses a self-adaption data analysis method for small-animal brain functional magenetic resonance imaging. The method includes the following steps that whole-brain scanning images ofall test animals are obtained multiple times, head movement correction is carried out, and whole-brain average images of all the animals are obtained; a whole-brain image of some animal serves as a reference image, image registration and image averaging are iteratively carried out, and a self-adaption brain template is obtained; in-brain pixels of the self-adaption brain template are extracted ina multichannel gaussian filter mode to serve as original in-brain-pixel mask images; in-brain-pixel mask images matched with self-adaption brain template space are obtained; all test individual brainimages and the self-adaption brain template are subjected to space standardization, and skull peeling is carried out; time sequences of all interest areas of all the test animals are obtained; throughthe pearson correlation algorithm, correlation indexes between all the interest areas are obtained, and a whole-animal network of the test animals is obtained. The technical scheme is wide in adaptation and high in efficiency, and is not influenced by artificial subjective factors.

Description

technical field [0001] This application generally relates to the technical field of magnetic resonance image processing, and in particular to an adaptive small animal brain functional magnetic resonance imaging data analysis method. Background technique [0002] Small animal experiments play an irreplaceable role in neuroscience research, such as the development of new drugs, the study of the pathogenesis of severe brain diseases, etc., all need to use appropriate animal models for experiments. In vivo small animal brain functional magnetic resonance imaging (Functional Magnetic Resonance Imaging, fMRI) technology enables researchers to dynamically observe small animal brain functional activities, and provides a powerful means for the study of small animal brain functional activities and brain functional networks. At present, the analysis method based on manually delineating the region of interest (Region Of Interest, ROI) is commonly used, that is, the researchers delineate...

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Application Information

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IPC IPC(8): G06T7/33G01R33/58
CPCG01R33/58G06T7/337G06T2207/10088G06T2207/30016
Inventor 聂彬彬王杰叶松涛刘华单保慈
Owner INST OF HIGH ENERGY PHYSICS CHINESE ACADEMY OF SCI
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