MPI image segmentation method, system and device based on local maximum point threshold expansion

Abstract

The invention belongs to the field of MPI image segmentation, particularly relates to an MPI image segmentation method, system and equipment based on local maximum point threshold expansion, and aims to solve the problems. The MPI image segmentation method comprises the steps of distinguishing a foreground signal and a background signal of a to-be-segmented MPI image based on a threshold segmentation method; the foreground MPI image signals are clustered through a K-means clustering method, and different types of clusters are obtained; selecting neighborhood pixels of each cluster center setting area, and obtaining the position of a local maximum signal intensity point of each cluster; based on the position of the local maximum signal intensity point of each cluster, combining the signal intensity corresponding to each position, performing threshold expansion operation, and obtaining an expansion area of each cluster; and combining the expansion regions of the clusters to obtain a segmentation result of the MPI image to be segmented. According to the threshold expansion MPI image segmentation method based on the local maximum point, robust and accurate MPI image segmentation is realized, and the influence of selectivity deviation existing in MPI image segmentation is reduced.

Description

technical field [0001] The invention belongs to the field of MPI image segmentation, and in particular relates to an MPI image segmentation method and system based on local maximum point threshold expansion. Background technique [0002] Magnetic particle imaging (MPI, Magnetic particle imaging) is an emerging method to directly detect the magnetization of iron oxide nanoparticles, which has the advantages of high specificity and sensitivity, linear quantitative ability, and high clinical translation potential. In various fields of biomedical research, this relatively novel imaging modality has sparked scientific inquiry in the new advanced field of molecular imaging and analysis, and has shown remarkable advances in the development of therapeutics and precision medicine. It relies on superparamagnetic iron oxide (SPIO) nanoparticle signals to generate positive-contrast images, setting a new standard for quantitative biological imaging. [0003] However, since MPI imaging i...

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Problems solved by technology

[0005] In order to solve the above-mentioned problems in the prior art, that is, there is a selectivity deviation in the existing MPI image segmentation, resulting in poor quality of the MPI image segmentation, the present invention provides an MPI image segmentation method based on threshold expansion of local maximum points, which MPI image segmentation methods include:

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