Fuzzy-connectedness-algorithm-based segmentation method of thalamus and substructures of thalamus

Abstract

The invention relates to a-fuzzy-connectedness-algorithm-based segmentation method of the thalamus and substructures of the thalamus. The method comprises the steps of inputting an original image, pre-processing the original image, automatically extracting an interesting area where a nucleus is located, estimating a mean value and a standard deviation in the area, calculating the fuzzy affinity to a seed point of the periphery region of the seed point, and conducting post-processing. According to the fuzzy-connectedness-algorithm-based segmentation method, the interesting area is automatically selected by adopting the confidence connectedness; when the fuzzy connectedness is calculated, gradient features are added on the basis that only gray features are used in the prior art, and the edge of the image can be expressed better. Experiment results show that the fuzzy-connectedness-algorithm-based segmentation method effectively reduces the frequency of segmentation-free phenomenon of a traditional fuzzy connectedness algorithm; weight coefficients between the gray features and the gradient features are obtained through self-adaption calculation, and accuracy of segmentation results is increased. According to the fuzzy-connectedness-algorithm-based segmentation method, automatic selection of fuzzy connectedness segmentation threshold values is achieved, the threshold values change along with changes of the seed point, and the degree of automation in a segmentation process is increased.

Description

technical field [0001] The invention belongs to the field of medical image processing, and relates to a method for automatically segmenting the thalamus and its substructure nerve nuclei based on MRI (Magnetic Resonance Image, nuclear magnetic resonance imaging) images, in particular to a thalamus and its substructure based on an improved fuzzy connectivity algorithm. Substructure segmentation method. Background technique [0002] With the development of modern medical technology, computer-assisted surgery of the cranium is widely used in clinic. At present, related technologies have used the thalamus and its substructure neural nuclei as the damaged area of ​​brain stereotaxic neurosurgery for the treatment of epilepsy and extrapyramidal diseases. The spatial relationship between the thalamus and its surrounding brain tissue is complex. With the development of imaging, the segmentation of the thalamus and its internal nuclei is still a difficult problem in imaging. Segmen...

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Problems solved by technology

[0004] Aiming at the lack of an effective automatic segmentation method for brain nuclei in the prior art, manual intervention is still required, and the segmentation process is cumbersome to operate, the present invention proposes a segmentation method for the thalamus and its substructures based on an improved fuzzy connectivity algorithm. By applying Confidence connectivity theory automatically obtains the region of interest of thalamic nuclei; introduces image gradient features within the framework of fuzzy connectivity; realizes adaptive weight adjustment of grayscale features and gradient features, and automatic selection of fuzzy connectivity segmentation thresholds; While reducing manual intervention, it ensures the accuracy of segmentation results and simplifies manual operations

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