Magnetic resonance image brain structure automatic dividing method based on statistics multi-map registration optimization

A technology for automatic segmentation of magnetic resonance images, applied in the field of medical image processing, can solve problems affecting segmentation results

Inactive Publication Date: 2012-08-22
INST OF AUTOMATION CHINESE ACAD OF SCI
View PDF2 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

These registration methods are subject to the influence of image acquisition quality and target differences in the image, which indirectly affects the final segmentation results.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Magnetic resonance image brain structure automatic dividing method based on statistics multi-map registration optimization
  • Magnetic resonance image brain structure automatic dividing method based on statistics multi-map registration optimization
  • Magnetic resonance image brain structure automatic dividing method based on statistics multi-map registration optimization

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0017] The detailed problems involved in the technical solutions of the present invention will be described in detail below with reference to the accompanying drawings. It should be pointed out that the described embodiments are only intended to facilitate the understanding of the present invention and do not have any limiting effect.

[0018] The present invention is the automatic segmentation of T1-weighted three-dimensional magnetic resonance brain images. like figure 1 As shown, images 102, 104 show the input images required to segment the brain image, where 102 is an axial view of a one-layer T1-weighted 3D MRI brain image, and 104 is a set of manually segmented atlases .

[0019] The invention proposes a segmentation method based on iterative statistical multi-atlas under the framework of multi-atlas segmentation. Using a set of images with manual segmentation results as the atlas, the traditional statistical multi-atlas method is used to initially segment the image t...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a magnetic resonance image brain structure automatic dividing method based on statistics multi-map registration optimization. A manual image dividing method is utilized for obtaining a plurality of maps; the maps are registered to images to be divided one by one; the images to be divided are subjected to initial dividing; the initial dividing images are subjected to iteration optimization processing; a registration field between each map and the images to be divided is calculated by using multi-channel image registration, and the registration field is used for registering the images of the maps and the dividing results to image spaces to be divided; and the final dividing results are calculated. The iteration method is utilized for simultaneously optimizing the registration precision of the maps and the dividing images and the dividing results of the images to be divided, so that the final dividing results are obviously superior to those of the traditional multi-map dividing method.

Description

technical field [0001] The invention relates to the technical field of medical image processing, in particular to a method for automatic segmentation of three-dimensional magnetic resonance brain images. Background technique [0002] In the basic and clinical research of medical imaging, the segmentation of magnetic resonance brain images is of great significance. Reliable and accurate segmentation of the brain is widely used in many medical imaging applications, such as surgical planning, disease course studies, and brain development in the elderly or young. Brain segmentation involves segmenting brain tissue and brain structures. In traditional research, segmentation results obtained by manual calibration of brain MRI images by trained experts are the gold standard for image segmentation. However, this method is very time-consuming, especially as the dataset continues to grow, it becomes less and less feasible. In addition, manual calibration is also prone to introduce ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T5/50
Inventor 范勇郝永富蒋田仔
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap