Integrated positioning and segmenting method for corpus callosum and cerebellum

Abstract

The invention discloses an integrated positioning and segmenting method for corpus callosum and cerebellar earthworm. The method comprises the following steps: acquiring an initial corpus callosum search area of a human brain ultrasonic image; obtaining a corpus callosum average template and a cerebellar earthworm average template from the corpus callosum image and the cerebellar earthworm image;taking the corpus callosum average template as a search basis to carry out template size adaptive sliding window search to obtain a corpus callosum accurate search result; performing active contour model algorithm iteration based on the final search result of the corpus callosum, and segmenting the corpus callosum to obtain contour and position information of the corpus callosum; performing adaptive template size sliding window search by adopting a new similarity comparison algorithm so as to obtain a cerebellar earthworm fine search result; and iterating the initial contour to obtain an accurate contour of the cerebellar earthworm, and smoothing the accurate contour to finally obtain the accurate contour of the cerebellar earthworm.

Description

technical field [0001] The invention relates to the technical field of ultrasonic image processing and analysis, in particular to an integrated positioning and segmentation method for corpus callosum and cerebellar vermis. Background technique [0002] With the widespread application of computer technology in medicine, the earlier manual labeling and segmentation of images has been gradually replaced by computer automatic algorithms. For how to detect and judge the fetal brain development, the development of the corpus callosum and cerebellar vermis is an important basis for judgment. At present, manual positioning and segmentation of the corpus callosum and cerebellar vermis in ultrasound images is usually used, and the contour length is calculated. , area and other characteristic information to detect and judge whether the fetal brain is developing normally. How to accurately and efficiently locate the corpus callosum and cerebellar vermis, and automatically segment them,...

AI Technical Summary

Problems solved by technology

At present, there is no known effective computer-integrated automatic processing method for the positioning and segmentation of the corpus callosum and cerebellar vermis in ultrasound images, and the positioning and segmentation are all done manually

This requires professional knowledge reserves, and it takes a lot of time, and the effect is not necessarily fine, so the accuracy cannot be guaranteed

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