Method for registering stereoscopic medical image rapidly, accurately and non-linearly based on sparse representation

A non-linear registration and sparse representation technology, applied in image analysis, image data processing, instruments, etc., can solve the problems of increased calculation cost and affecting interpolation accuracy, so as to improve registration speed, improve accuracy, and accelerate registration The effect of the process

Inactive Publication Date: 2014-07-09
FUDAN UNIV
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Problems solved by technology

The TPS method can achieve accurate interpolation when using a large number of marker points, but its computational cost will also increase significantly
On the other hand, the actual deformation on the anatomical structure may not completely conform to the TPS predefined model, which may affect the final interpolation accuracy

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  • Method for registering stereoscopic medical image rapidly, accurately and non-linearly based on sparse representation
  • Method for registering stereoscopic medical image rapidly, accurately and non-linearly based on sparse representation
  • Method for registering stereoscopic medical image rapidly, accurately and non-linearly based on sparse representation

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Embodiment 1

[0034] The goal of deformable-based registration is to register the target image S to the template image T. In many applications, a small number of P marker points or key points on the template image are usually first determined by manual labeling or an automatic marker point detector. The coordinates of these P template marker points can be stored in a long vector x, where Finally, in order to register the target image to the template image, it is necessary to estimate the corresponding points of the target image (stored in the vector y) from the marker points of the template image (stored in the vector x) L (S)) estimates its deformation field y D (S), here, the corresponding points and deformation fields defined by the present invention are all stored in the vector, and the present invention proposes a method based on machine learning to estimate the dense deformation field from discrete corresponding point vectors, that is, it is effective by means of sparse representation...

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Abstract

The invention belongs to the field of medical image analysis and application, relates to a method for registering a stereoscopic target image to a template image, and specifically relates to the method for registering a stereoscopic medical image rapidly, accurately and non-linearly based on sparse representation. The sparse combination coefficient can be obtained by utilizing detected mark corresponding points of the template image and the target image and by searching an established deformation field dictionary and corresponding point dictionary. The coefficient can fuse corresponding examples of the deformation field dictionary, so that a final deformation field of the target image is obtained, and the target image is registered to the template image. The method has a relatively-good application in a clinic environment and can be used for registering brain nuclear magnetic resonance images rapidly and accurately in neurosciences, or used for accurately positioning the position of the prostate in prostate cancer radioactive therapy, and can realize more accurate registering more rapidly.

Description

technical field [0001] The invention belongs to the field of medical image analysis and application, and relates to a method for registering a three-dimensional target image to a template image, in particular to a method for fast and accurate non-linear registration of a three-dimensional medical image based on sparse representation, and the method has good application in clinical environments , which can be used in neuroscience to quickly and accurately register MRI images of the brain, or to pinpoint the location of the prostate gland in radiotherapy for prostate cancer. Background technique [0002] It is disclosed in the prior art that it is a common problem in the field of medical image registration to generate a dense deformation field of the entire image through interpolation of a small number of sparse corresponding points. For example, in feature-based image registration, a set of landmarks is usually first automatically determined by a robust feature matching metho...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 史勇红宋志坚吴国荣沈定刚
Owner FUDAN UNIV
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