Medical sequence image motion estimation method based on generalized fuzzy gradient vector flow field

Abstract

The present invention discloses a medical sequence image motion estimation method based on the generalized fuzzy gradient vector flolw field, it includes the following steps: 1. obtaining and sequence image; 2. obtaining generalized fuzzy gradient vector flow field of double-step tracking model, and locak correlation of generalized fuzzy gradient vector flow field and optical flowvector field; 3. manually drawing the outline of edge of interested zone of first frame image; 4. under the action of three kinds of external force fields using said double-step tracking model to frame-by-frame track the drawn edge outline of interested zone; 5. combining the above-mentioned tracking result of outline, and using maximum posteriori estimation to make optimizational estimation and tracking of every point on the outline so as to obtain the optimum motion track of the point.

Description

technical field [0001] The invention relates to an image processing method, in particular to a method for estimating the movement of medical sequence images reflecting the contraction and relaxation movements of human heart and lung organs and blood vessels. Background technique [0002] In the fields of medical image post-processing and image-guided computer-assisted surgery (IGS), the deformation and motion estimation of biological soft tissues based on medical image sequences is an important research content. [0003] Comprehensive research on motion estimation and tracking problems in computer vision began in the early 1980s. After continuous in-depth development, many motion state estimation and tracking technologies involving points, curve segments, contours and surfaces inside non-rigid bodies have emerged. In this field, it is of great practical significance to describe the space-time motion state of the region of interest, edge, or contour line in the sequence imag...

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Problems solved by technology

Literature [3] discloses that the gradient vector flow field (GVF) is used as a new external force condition to constrain the dynamic contour line in a single image. In this way, not only the selection of the initial dynamic contour line can have a larger dynamic range, but also can approach The edge depression area that cannot be reached by the pure gradient field, however, when using the gradient vector flow external force field to analyze the single-frame interest region of the heart, it is often encountered that the strong edge attracts and weakens the gradient vector flow field of the weak edge in the image, in fact ROI boundaries are often at weak edges, resulting in large tracking errors

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