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Possibility fuzzy C-means (FCM) algorithm-based magnetic resonance imaging (MRI) tumor image segmentation method and system

An image segmentation and possibility technology, applied in the field of medical devices, can solve problems such as cluster center sensitivity, noise and outlier sensitivity

Inactive Publication Date: 2016-11-16
TIANJIN UNIV
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Problems solved by technology

However, FCM also has some shortcomings. The sum of the membership degrees of the same sample belonging to all classes is 1, which makes it sensitive to noise and outliers; at the same time, it is sensitive to the initial cluster center.

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  • Possibility fuzzy C-means (FCM) algorithm-based magnetic resonance imaging (MRI) tumor image segmentation method and system
  • Possibility fuzzy C-means (FCM) algorithm-based magnetic resonance imaging (MRI) tumor image segmentation method and system
  • Possibility fuzzy C-means (FCM) algorithm-based magnetic resonance imaging (MRI) tumor image segmentation method and system

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[0069] The invention solves the brain tumor segmentation problem of MRI by using the cooperative possibility FCM algorithm under the framework of fuzzy set theory. In fuzzy set theory, FCM is an important research direction. The core idea of ​​FCM is to find the appropriate membership degree and cluster center, so that the variance and iteration error of the cost function in the cluster are minimized. The value of the cost function is from pixel to cluster Weighted cumulative sum of class centrality 2-norm measures. In order to overcome the shortcomings of the FCM algorithm, some scholars have proposed possible C-means clustering and weighted fuzzy C-means clustering. Due to the arbitrariness of the value of the membership degree, the clustering effect of these algorithms is not ideal, and the cluster centers are prone to overlap. Therefore, some scholars proposed the FCM algorithm based on the possibility of uncertain membership degree. This algorithm improves the effect of ...

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Abstract

The present invention relates to the medical apparatus and instruments technology field, and aims to provide a full-automatic brain tumor image segmentation technology which is combined with the MRI to generate images, executes an FCM algorithm via a software and realizes the image processing. Meanwhile, the full-automatic brain tumor image segmentation technology is combined with the advantages of a collaborative fuzzy clustering algorithm, so that the FCM algorithm can be applied to the MRI brain tumor images more effectively. The technical scheme adopted in the present invention is that: the possibility FCM algorithm-based MRI tumor image segmentation method and system is composed of an MRI device and a computer, the MRI device generates images to input to the computer, and the computer is equipped with the following modules: a denoising module used for removing the noise and the brain tissues in the MRI brain tumor images and carrying out the normalization to prepare for the next step; a histogram statistics module; an FCM initial segmentation module; a matrix adjusting module; an FCM segmentation image module which uses the collaborative possibility FCM algorithm to obtain the segmentation images. The possibility FCM algorithm-based MRI tumor image segmentation method and the possibility FCM algorithm-based MRI tumor image segmentation system of the present invention are mainly applied to the image segmentation occasions.

Description

technical field [0001] The invention relates to the technical field of medical equipment, is an important aspect in the field of medical imaging, and plays an important role in the fields of brain tumor cutting, brain tumor classification, and brain tumor identification. Specifically, it involves a method and system for MRI brain tumor image segmentation based on a possible FCM algorithm. Background technique [0002] With the continuous increase in the breadth and depth of clinical applications of medical images, medical images have become one of the important research directions in the field of medical image processing; especially the research on brain tumors has become a hot research topic in recent years. The incidence of brain tumors is relatively high, accounting for about 1.4% of systemic tumors, but the death rate is more than 2.4%. Therefore, only early detection and treatment in clinical practice can effectively reduce the huge harm caused by brain tumors to human ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62
CPCG06T2207/10088G06T2207/30096G06T2207/30016G06F18/23213
Inventor 童云飞李锵关欣
Owner TIANJIN UNIV
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