Dense connection asymmetric hierarchical network training method and cardiac motion field estimation method

A network training, asymmetric technology, applied in the field of image processing, to reduce the phenomenon of gradient disappearance, effectively use, and improve smoothness

Active Publication Date: 2019-08-20
SHENZHEN UNIV
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Problems solved by technology

[0006] The main purpose of the present invention is to provide a densely connected asymmetric hierarchical network training method and a cardiac motion field estimation method to solve the cardiac motion estimation problem of traditional Cine MR imaging and obtain a more stable and reasonable cardiac motion field

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  • Dense connection asymmetric hierarchical network training method and cardiac motion field estimation method
  • Dense connection asymmetric hierarchical network training method and cardiac motion field estimation method
  • Dense connection asymmetric hierarchical network training method and cardiac motion field estimation method

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[0049] In order to make the purpose, features and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described The embodiments are only some of the embodiments of the present application, but not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts belong to the scope of protection of this application.

[0050] It should be noted that, in this document, the term "comprising" or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also includes none other elements specifically listed, or also include elements inheren...

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Abstract

The invention discloses a dense connection asymmetric hierarchical network training method and a cardiac motion field estimation method, and aims to solve the problem of cardiac motion estimation by using a dense connection coding-decoded asymmetric deep learning network to extract multi-scale characteristics of a left ventricle in two adjacent time point Cine MR images, and fusing the multi-scalecharacteristics by the coding-decoded structure network to decide the displacement of the pixel point. The introduction of the dense connection network alleviates the gradient disappearance phenomenon, the left ventricle characteristics are more effectively utilized through the fusion of the left ventricle characteristics, and fewer network parameters are provided. Wherein the asymmetric networkstructure can obtain sparse deformation fields at equal intervals, and the B spline interpolation is further utilized to obtain a smooth dense deformation field. The distortion energy constraint of the deformation field is introduced into the objective function of network training, the smoothness of the deformation field is improved, and a more stable and reasonable heart motion field can be obtained to be used for quantitative analysis of cardiovascular diseases.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a densely connected asymmetric hierarchical network training method and a heart motion field estimation method. Background technique [0002] Using heart images to analyze its anatomical structure and movement changes plays an important role in the diagnosis of heart diseases, and is an important means of diagnosing heart diseases and formulating treatment plans. Cardiac motion estimation uses heart image sequences at different time points to estimate the heart deformation function, and then fits the continuous motion model of the heart through interpolation. Using this continuous motion model, it is possible to estimate the state of the heart at any time, complete accurate quantification of cardiovascular structure and function, describe the cardiac output, ejection fraction, myocardial strain and other indicators of the heart during exercise, and predict the location o...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/207G06T7/246
CPCG06T2207/10088G06T2207/20081G06T2207/20084G06T2207/30048G06T7/207G06T7/246
Inventor 甘梓誉杨烜裴继红杨博乾
Owner SHENZHEN UNIV
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