A method for automatic segmentation of serialized visual human body slice images

Abstract

The invention discloses a method for automatically segmenting a serialized visible human body slice image, which comprises the following steps: S1: selecting a serialized image of a color organ slice image; S2: using a minimum cut algorithm based on an optimized energy function to perform a foreground region on the image Segment processing with the background area; S3: extract the seed point image of the foreground area in the image based on the corrosion algorithm; S4: extract the skeleton image of the background area in the image based on the thinning algorithm; S5: extract the seed point image of the foreground area and the background area The second image of the skeleton segmentation serialized image. This method combines two segmentation methods, interactive segmentation and serialized automatic segmentation, which can not only reduce the robustness of segmentation affected by the complexity of medical images, but also greatly save segmentation time. It has very important practical significance in the field of medical work such as the quantitative analysis of the lesion area.

Description

technical field [0001] The invention relates to the technical field of image segmentation, in particular to a method for automatic segmentation of serialized visible human body slice images. Background technique [0002] In recent years, the research on visible human has deepened day by day, making it possible to use the visible human dataset and apply it to practical research. Manually extracting the desired tissues or organs during the 3D redrawing process of the dataset consumes a lot of manpower. Traditional image automatic segmentation algorithms cannot quickly and accurately segment different human tissues with very similar colors. The serialized automatic segmentation method based on spectral analysis and skeleton graffiti can identify the subtle color differences between tissues, and quickly, accurately and effectively separate the human tissues and organs required for research from the huge data set. Provide a reliable source of data for future medical research. ...

AI Technical Summary

Problems solved by technology

However, in this process, technicians need to repeatedly search for the best marked area, and depending on the implementer, the obtained segmentation results are also uneven.

The seed point of the first image is particularly important, which may directly affect the subsequent results, and the extraction of the region of interest in the image has a lot of interference. If the non-interest region has similar pixels to the region of interest, it can also be extracted. Therefore, the subsequent seed point There is a certain error in the transmission

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