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Medical image clustering method based on entropy

A medical image and clustering method technology, applied in the field of medical information, can solve the problem of sensitive parameter selection, and achieve the effect of reducing the clustering time

Inactive Publication Date: 2015-12-09
HARBIN ENG UNIV
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  • Claims
  • Application Information

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Problems solved by technology

However, the above algorithms need to specify parameters in the process of application, and are also very sensitive to the selection of parameters.

Method used

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  • Medical image clustering method based on entropy
  • Medical image clustering method based on entropy
  • Medical image clustering method based on entropy

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Embodiment Construction

[0020] Below in conjunction with accompanying drawing and specific implementation the present invention will be further described:

[0021] The present invention comprises the steps:

[0022] (1) Image preprocessing process: extract the region of interest (ROI, RegionOfInterest) from the original medical image, calculate the gray histogram of the ROI region of the image, obtain the valley list of the gray histogram of the ROI region of the image, and process the image according to the valley list Extract texture features hierarchically, standardize the obtained graded texture image to a uniform size according to actual needs, and then divide the texture image into several regions, and compare the sum of the differences between the LBP (LocalBinaryPatterns) histograms of the corresponding regions of the two images. Measure the degree of similarity between medical images;

[0023] (2) The sparse process of the graph: the medical image set is abstracted into a weighted undirecte...

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Abstract

The invention belongs to the technical field of medical information, and specifically relates to a medical image clustering method based on entropy. The method provided by the invention comprises the steps that (1) an image to be clustered gives a clustering request; (2) an image is pre-processed; (3) the image is thinned; (4) weighted undirected image clustering is carried out based on entropy; and (5) a result is shown. According to the invention, the entropy method is used to carry out medical image clustering; a medical image set is abstracted into a full image; thinning pruning is carried out on the full image; left sides show that two images are very similar with each other; the weighted undirected image clustering method is provided; through the processes, medical image clustering is realized; the clustering time can be effectively reduced; the clustering accuracy is not significantly reduced; and the method helps a doctor to diagnose the condition of a patient in daily work.

Description

technical field [0001] The invention belongs to the technical field of medical information, and in particular relates to a medical image clustering method based on graph entropy. Background technique [0002] With the rapid development of science and technology, the modernization of medical and health services has been deepening. Medical imaging technology, such as: computer X-ray tomography (CT), positron emission tomography (PET), magnetic resonance imaging (MRI), etc., can assist doctors in diagnosing patients' conditions. The process is heavily used, so hospitals generate a large number of medical images every day. How to make good use of these medical images, and dig out valuable information from the back of these images, so as to facilitate doctors to diagnose patients' conditions, is currently a hot spot in data mining of medical images. At present, the research on data mining of medical images mainly focuses on the classification, clustering, similarity search and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/40G06F17/30
CPCG06F16/35G06T2207/10081G06T2207/10088G06T2207/10104
Inventor 潘海为战宇韩启龙谢晓芹张志强吴枰
Owner HARBIN ENG UNIV
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