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Organ auxiliary positioning segmentation method based on statistical deformation model

A deformation model and auxiliary positioning technology, applied in the field of medical imaging, can solve the problems of high complexity, low efficiency, and large workload of organ image segmentation

Active Publication Date: 2016-06-29
NORTHWEST UNIV(CN)
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Problems solved by technology

[0006] In order to solve the problems of large workload, high complexity and low efficiency of organ image segmentation, the present invention proposes an organ-assisted localization and segmentation method based on statistical deformation model

Method used

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  • Organ auxiliary positioning segmentation method based on statistical deformation model
  • Organ auxiliary positioning segmentation method based on statistical deformation model
  • Organ auxiliary positioning segmentation method based on statistical deformation model

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Embodiment Construction

[0052] The present invention will be further described in detail below in conjunction with the accompanying drawings. It should be noted that the described embodiments are only intended to facilitate the understanding of the present invention, rather than limiting it in any way.

[0053] The present invention will be further described below in conjunction with accompanying drawing:

[0054] Step 1: Obtain mouse CT tomographic data:

[0055] Fix the experimental mice injected with the contrast agent on the imaging table of the Micro-CT imaging system, adjust the positions of the X-ray tube, the rotating table and the X-ray flat panel detector so that the centers of the three are in a straight line, and perform 360-degree imaging on the mice. High-degree irradiation scanning, acquisition of projection data, and three-dimensional reconstruction of projection data by filter back projection method to obtain mouse CT tomographic data.

[0056] The mouse CT volume data used in the e...

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Abstract

The invention discloses an organ auxiliary positioning segmentation method based on a statistical deformation model. The method comprises the following steps: 1, obtaining CT data of an organism; 2, dividing high and low-comparison organs, selecting training samples in the CT data and extracting corresponding statistical prior information; 3, establishing the statistical deformation model of the low-comparison organs; 4, based on correlation between the high-comparison organs and the low-comparison organs, assisting in positioning initial positions of the low-comparison organs by means of the high-comparison organs; and 5, based on auxiliary positioning, carrying out search segmentation of the organs along a mark point normal direction. By use of the organ segmentation method provided by the invention, the initial positions of the organs can be automatically and rapidly sought, such prior information as the positions, shapes and the like of the tissue organs is integrated by use of the statistical deformation model, segmentation of the organs is rapidly and systemically completed, the image segmentation efficiency is greatly improved, and the method is an effective organ segmentation method.

Description

technical field [0001] The invention belongs to the field of medical imaging, and relates to an organ auxiliary positioning and segmentation method based on a statistical deformation model. Background technique [0002] Medical image segmentation plays an extremely important role in modern medical research, clinical diagnosis, pathological analysis and treatment. It is a prerequisite for biomedical image analysis and a necessary step for human beings to understand the structure and function of tissues and organs. However, due to the diversity and complexity of human organs, the segmentation problem has always been a hot issue for researchers to explore. [0003] Commonly used methods in image segmentation include: edge detection method, threshold segmentation method, region growing method, active contour model method, etc. However, these methods have their own limitations: the edge detection method describes the process of grayscale change in the image based on the physical...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/60
CPCG06T7/60G06T2207/10004G06T2207/30004
Inventor 侯榆青王宇慧赵凤军贺小伟郭红波高培
Owner NORTHWEST UNIV(CN)
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