Three-dimensional nonlinear registration method and system for massive brain image data set

Abstract

The invention relates to a three-dimensional nonlinear registration method and system for a massive brain image data set. The three-dimensional nonlinear registration method of the massive brain imagedata set includes the following steps of: S0, down-sampling; S1, low-resolution image registration; and S2, high-resolution image fast transformation. The low-resolution image registration step further includes the following steps of S11, linear registration; and S12, nonlinear registration. The high-resolution image fast transformation step further includes the following steps of: S21, transformation matrix calculation for high-resolution registration; S22, post-high-resolution registration spatial range calculation; S23, blocking; and S24, high-resolution nonlinear transformation. Accordingto the three-dimensional nonlinear registration method and system for the massive brain image data set of the invention, the registration information of low-resolution image data is adopted to transform the massive high-resolution three-dimensional image data set, so that the nonlinear registration of the massive high-resolution three-dimensional image data set can be realized. The method and system of the invention are applicable to all linear registration based on transformation matrices and all nonlinear registration based on displacement fields and can quickly perform nonlinear registration on TB-level data sets.

Description

technical field [0001] The invention relates to image processing technology, in particular to a three-dimensional non-linear registration method for massive brain image data sets. Background technique [0002] As an important research direction in the field of image processing, image registration technology is widely used in remote sensing, automatic navigation, pattern recognition, computer vision, biomedicine and other fields. With the advent of the era of big data, massive 3D image data sets continue to increase, often reaching TB level. How to perform nonlinear registration on these massive 3D datasets is a very big challenge. [0003] In the Chinese invention patent specification CN104361590, a high-resolution remote sensing image registration method with adaptive distribution of control points is proposed. The control points are extracted, and then the normalized mutual information measure NMI is used to match the control points at multiple scales. However, the data...

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