Method and device for extracting intracerebral brain tissue

Abstract

The invention provides a method and a device for extracting an intracerebral brain tissue. The method comprises the following steps: (1) inputting an image, preprocessing the image for obtaining a smooth image and a skin mask, and performing binarization on the smooth image for obtaining a binary image; (2) according to a current corrosion radius, performing morphological erosion on the binary image for obtaining N current connected domains; (3) determining a human neck position through the skin mask, and determining a current final dividing result according to the N current connected domains and the human neck position; and (4) performing dividing leakage detection on the current final dividing result, if a leakage occurs in the current final dividing result, enlarging the current corrosion radius and returning to the step (2); and if no leakage occurs in the current final dividing result, determining the current final dividing result as the intracerebral brain tissue which requires extraction. The method and the device can be used for automatically and accurately extracting the intracerebral brain tissue and furthermore have advantages of low realizing complexity and high computing speed.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method and device for extracting intracranial brain tissue. Background technique [0002] In preparation for radiation therapy, doctors use medical images of the patient to calculate the radiation path and dose used during radiation therapy. During this process, doctors need to outline some important organs in medical images so that they can avoid radiation exposure during radiotherapy or reduce the radiation dose they receive. Especially for head CT images, the internal structure of the cranial cavity is often an area of ​​interest for doctors. Intracranial brain tissue includes three large blocks of nerve fibers: the cerebrum, cerebellum, and brainstem, which are closely related to human intellectual activities and are important areas that must be protected during radiotherapy. Therefore, when segmenting head CT images, how to quickly and accurately extract intracranial brai...

AI Technical Summary

Problems solved by technology

The problem with most of these methods is that the processing of ideal CT slices does not take into account the partial volume effect, gray overlap, etc., and cannot obtain satisfactory segmentation results for the case where the skull is not closed.

However, this type of method cannot perform image segmentation alone. It should be used in combination with other methods, generally as post-processing of other methods, and how to adaptively determine the appropriate algorithm scale is very important when using such methods. The problem

[0006] The region growing method, the region growing method based on the seed point has a strong dependence on the seed point, and needs to manually or automatically select one or more seed points, the degree of automation is low, and the whole process is more complicated

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