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lung CT image nodule screening method based on generalized S transformation and Teager attributes

A CT image and screening method technology, applied in image analysis, image data processing, instruments, etc., can solve the problem of not using nodule frequency information, and achieve the goal of improving the nodule screening accuracy, distinguishing degree, and improving accuracy. Effect

Active Publication Date: 2019-05-31
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to: aim at the problem that the nodule screening method in the existing lung CT images only utilizes the spatial grayscale information and morphological information of the nodules, and does not utilize the frequency information of the nodules, and provides a method based on The generalized S-transform and Teager attribute lung CT image nodule screening method uses the time-frequency spectrum obtained by the generalized S-transform to extract Teager principal energy information from the time-frequency spectrum, providing a new screening method for the lung CT image nodule screening method , real-time frequency analysis method for nodule screening by Teager energy

Method used

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  • lung CT image nodule screening method based on generalized S transformation and Teager attributes
  • lung CT image nodule screening method based on generalized S transformation and Teager attributes

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Embodiment 1

[0138] Such as figure 1 As shown, a lung CT image nodule screening method based on generalized S transform and Teager attributes, including the following steps:

[0139] Step 1: Perform generalized S-transformation on the input lung CT image in the horizontal direction and vertical direction to obtain the time spectrum in the horizontal direction and the time spectrum in the vertical direction;

[0140] Step 2: Carry out the extraction of Teager principal energy to described horizontal direction time spectrum and vertical direction time spectrum, obtain horizontal direction Teager principal energy figure and vertical direction Teager principal energy figure;

[0141] Step 3: performing threshold segmentation on the Teager principal energy map in the horizontal direction and the Teager principal energy map in the vertical direction to obtain suspected nodules;

[0142] In step 1, the input lung CT image is preprocessed, and the preprocessing includes determining the value rang...

Embodiment 2

[0167] Based on embodiment 1, step 1: carry out the generalized S transform on the horizontal direction and vertical direction to the input lung CT image, obtain the time spectrum in the horizontal direction and the time spectrum in the vertical direction, including the following steps:

[0168] Step 1.1: Initialize the frequency variable in the horizontal direction and the frequency variable in the vertical direction: the details are as follows:

[0169] When calculating the generalized S-transform of a one-dimensional signal in the i-th row in the horizontal direction, initialize the horizontal frequency variable f x = 0, f x The value range is from 0 to m, and m represents the length of the one-dimensional signal sigh in the i-th row in the horizontal direction;

[0170] When calculating the generalized S-transformation of the one-dimensional signal in the jth column in the vertical direction, initialize the frequency variable f in the horizontal direction y = 0, f y The...

Embodiment 3

[0183] Based on embodiment 1, step 2: the extraction of Teager principal energy is carried out to described horizontal direction time spectrum and vertical direction time spectrum, obtain horizontal direction Teager principal energy diagram and vertical direction Teager principal energy diagram, comprise the steps:

[0184] Step 2.1: Initialize positional parameters, specifically:

[0185] When the horizontal direction is initialized, the variable x=2, x∈2~m-1, m represents the length of the one-dimensional signal sigh of the i-th row in the horizontal direction;

[0186] When the vertical direction is initialized, the variable y=2, y∈2~n-1, n represents the length of the jth column of one-dimensional signal sigv in the vertical direction;

[0187] Step 2.2: obtain the time spectrum S (t, f, p) when the frequency is f according to step 1.5, calculate the TK energy, and its calculation formula is as follows:

[0188] retk(t, f) = re(S(t, f, p)) 2 -re(S(t-1, f, p))*re(S(t+1, f...

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Abstract

The invention discloses a lung CT image nodule screening method based on generalized S transformation and Teager attributes, and belongs to the field of lung image processing. The method comprises thesteps of 1, performing generalized S transformation in the horizontal direction and the vertical direction on an input lung CT image to obtain a time-frequency spectrum in the horizontal direction and a time-frequency spectrum in the vertical direction; Step 2, extracting Teager main energy from the horizontal-direction time-frequency spectrum and the vertical-direction time-frequency spectrum toobtain a horizontal-direction Teager main energy map and a vertical-direction Teager main energy map; Step 3, performing threshold segmentation on the Teager main energy diagram in the horizontal direction and the Teager main energy diagram in the vertical direction to obtain suspected nodules; According to the method, the main energy attribute of the Teager is calculated through generalized S transformation; The difference between the nodules and the non-nodule areas is analyzed from the perspective of time-frequency analysis, the influence of the lung boundary of the lung CT image on generalized S transformation is overcome by searching for non-zero pixels, the suspected nodule areas are screened out by utilizing the difference of the Teager main energy attributes in the time-frequencyspectrum, and the screening accuracy is improved.

Description

technical field [0001] The invention belongs to the field of lung image processing, in particular to a lung CT image nodule screening method based on generalized S transform and Teager attributes. Background technique [0002] The generalized S transform is a time-frequency analysis method. For non-stationary signals, the time-frequency analysis method can analyze the frequency components of the signal and locate the position of the frequency components; The Liye transform has better time-frequency resolution, no interference from Wigner-Ville cross terms, and has a wider adjustable frequency resolution than the S-transform. Therefore, the generalized S-transform has better flexibility and higher time-frequency resolution. [0003] The Teager main energy attribute is based on the improvement of the Teager-Kaiser (TK) energy, which can track and extract the local energy transformation of the signal. Compared with the disadvantage of TK energy that can only be calculated in a...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/11G06T7/13G06T7/136G06T7/168
Inventor 孙翎马彭真明蒲恬蒲红赵学功郭璐王卓然袁国慧唐雨潇范文澜陈江华
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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