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Method for fast clustering medical sequential images

A technology of sequence image and clustering method, applied in the field of rapid clustering of medical sequence images, can solve the problems of slow processing speed, poor clinical practicability, and low clustering accuracy, and achieve fast processing speed, strong clinical practicability, and clustering The effect of high class precision

Active Publication Date: 2014-03-26
SHANDONG UNIV
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Problems solved by technology

[0003] Aiming at the disadvantages of the previous methods described in the background technology, such as slow processing speed, low clustering accuracy, and poor clinical practicability, the present invention proposes a fast clustering method for medical sequence images, which first linearly transforms the original sequence image data in the measurement space into In the feature space, clustering is performed in the feature space, and finally the clustered data in the feature space are mapped back to the measurement space one by one to realize the clustering of the measurement space

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  • Method for fast clustering medical sequential images

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[0029] A fast clustering method for medical sequence images, which is implemented by CT (Computed Tomography) imaging workstations, such as figure 1 As shown, the steps are as follows:

[0030] S1) Pretreatment

[0031] CT import serial images, observe the serial images, and determine the classification number;

[0032] S2) Obtain the eigenvectors of the substances to be classified to form an eigenvector matrix

[0033] The method to obtain the feature vector of the substance to be classified is: assuming that there are n frames of serial images in the measurement space, divide the substance into k categories, and select d points of the K-th substance on the Nth frame {x 1 ,x 2 ,...,X d }, define the characteristics of this type of substance on the frame of image as:

[0034] Similarly, select and calculate the characteristics of this type of substance on other frames, and form the feature vector of this type of substance. Use the same method to obtain the feature vector of other typ...

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Abstract

A method for fast clustering a medical sequential images belongs to the technical field of computer aided diagnosis of medical imaging, and comprises the following steps of: preprocessing, forming a feature vector matrix, forming a target vector matrix, computing a linear transformation matrix, measuring a space vector feature space transformation, clustering a feature space, and clustering a measuring space. The method has high image processing speed, high clustering precision and strong clinical utility.

Description

Technical field [0001] The invention relates to the technical fields of medical image processing and imaging computer-aided diagnosis, and in particular to a fast clustering method for medical sequence images. Background technique [0002] With the increasing demand for clinical application of imaging diagnosis and the development of medical imaging technology, medical imaging data more commonly exists in the clinic in the form of massive, two-dimensional or three-dimensional sequence images. For medical sequence images, doctors are often only interested in one or several types of substances, which makes it particularly clinically meaningful to seek related clustering methods. According to investigations, a small number of researchers have done research on the clustering of medical sequence images, for example, Jiawan Zhang et al. in the article "Automatic Classification of MRI Images for Three-dimensional Volume Reconstruction by Using General Regression Neural Networks, 2004" ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N3/02
Inventor 孙丰荣张新萍宋尚玲曲怀敬
Owner SHANDONG UNIV