Image quality assessment method for electrical impedance tomography based on fuzzy c-means clustering

A technology of image quality evaluation and mean value clustering, which is applied in image analysis, image enhancement, image data processing, etc., can solve the problems that the conductivity is difficult to obtain and cannot be used, and achieve the effect of good adaptability

Active Publication Date: 2021-04-02
TIANJIN UNIV
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Problems solved by technology

However, in practical applications, the actual conductivity is difficult to obtain, so the current image quality evaluation methods cannot be used

Method used

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  • Image quality assessment method for electrical impedance tomography based on fuzzy c-means clustering
  • Image quality assessment method for electrical impedance tomography based on fuzzy c-means clustering
  • Image quality assessment method for electrical impedance tomography based on fuzzy c-means clustering

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Embodiment Construction

[0042] Considering the characteristics of low resolution, large artifacts, and blurred boundaries of EIT images, EIT images should meet the following conditions:

[0043] 1) The same medium should have the same gray scale;

[0044] 2) The grayscale of the target should be higher than the grayscale of the artifact, and the grayscale of the background should be lower than the grayscale of the artifact;

[0045] 3) The artifacts in the image should be as small as possible.

[0046] To sum up, the smaller the image artifacts and the higher the uniformity of the target and background, the better the image quality. Therefore, the final image quality evaluation index is obtained by fusing the size of artifacts and image uniformity. The present invention selects fast FCM clustering method for use, and reason is as follows:

[0047] 1) Fast FCM clustering can well deal with the problem of unclear boundaries in the image;

[0048] 2) The fast FCM method has a fast running time, has ...

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Abstract

The present invention relates to a method for evaluating the image quality of electrical impedance tomography based on fuzzy C-means clustering. Artifact class, target class and background class, but at this time the corresponding relationship between these three types of data and the class they belong to is unknown; the second part, the statistical classification results; calculate the average value of the gray value of the three types of pixels, according to the order from large to small The order of the three types of data is marked as target, artifact and background in turn; the third part is to calculate the evaluation index: calculate the proportion of artifacts according to the number of pixels of the artifact, and calculate the image uniformity according to the number and dispersion of pixels of the target and background ; Calculate the weights of the two indicators according to the degree of membership; multiply the two indicators by their respective weights and add them together to obtain the final image quality evaluation index λ; the artifact ratio index R obtained above, the uniformity index E and The index λ obtained after weighted addition can be used to evaluate the quality of EIT images.

Description

technical field [0001] The invention relates to a method for evaluating the image quality of electrical impedance tomography. Background technique [0002] Electrical impedance tomography (EIT) technology is a process detection technology developed based on electromagnetic field theory. It has the advantages of non-invasive, non-radiation, high real-time performance, and low cost. It can perform pathological detection and bedside monitoring on the human body. It has broad application prospects. [0003] EIT technology usually requires a set of electrode arrays, usually 16 or 32. These electrodes are in contact with the surface of the object to be measured, and by applying a weak current or voltage, the response electrical information is obtained from the corresponding detection electrodes, and then the image of the conductivity distribution in the area to be measured is obtained through an image reconstruction algorithm. Due to the low resolution, EIT images usually have t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T11/00G06K9/62
CPCG06T7/0012G06T11/005G06T2207/30168G06T2207/10072G06F18/23
Inventor 王泽莹岳士弘刘笑远
Owner TIANJIN UNIV
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