Method and device for abdomen soft tissue nuclear magnetism image segmentation

Abstract

The invention discloses a method and device for abdomen soft tissue nuclear magnetism image segmentation. The method comprises the steps that an original outline is initialed near an objective outline; a morphological operator is used for carrying out expansion and corrosion operations on the original outline, and a band-shaped closed area is formed in and outside the objective outline to be segmented; KPCA training is conducted on a collected shape template and prior shape information is obtained through a statistics model; the prior shape information is combined with data items of an energy function of a nuclear magnetism image segmentation model, and an energy function is constructed; a kernel Graph cuts algorithm is used for carry out segmentation on the band-shaped closed area and an objective outline is obtained. The method and device for abdomen soft tissue nuclear magnetism image segmentation can achieve semi-automatic segmentation, the device is simple, the robustness of the nuclear magnetism image segmentation algorithm is effectively improved so as to enable the segmentation result to be more accurate, and the method and device for abdomen soft tissue nuclear magnetism image segmentation can be applied to most nuclear magnetism image segmentation.

Description

technical field [0001] The invention relates to the field of organ tissue segmentation algorithms for abdominal nuclear magnetic images, in particular to a method and device for abdominal soft tissue nuclear magnetic image segmentation. Background technique [0002] Magnetic resonance imaging (magnetic resonance imaging, MRI) uses radio frequency (radio frequency, RF) electromagnetic waves to excite substances containing atomic nuclei with non-zero spins in a magnetic field, and nuclear magnetic resonance (nuclear magnetic resonance, NMR) occurs. A digital image is established by collecting magnetic resonance signals with induction coils and processing them according to certain mathematical methods. The NMR signal intensity is related to the density of hydrogen nuclei in the sample. Two-thirds of the weight of the human body is water, and different tissues have different proportions of water molecules, so the NMR signal intensity is also different. This difference is used as...

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Problems solved by technology

[0009] The existing image algorithm only relies on the gray information of the image to segment, and cannot obtain ideal results, and the complexity of medical images and the characteristics of little gray change between different tissues make it very difficult to segment a specific tissue alone. The primary purpose of the present invention is to provide a method for segmenting abdominal soft tissue MRI images, which improves the robustness of the MRI image segmentation algorithm and makes the segmentation results more accurate

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