Method for extracting texture based on lung nodules three orthogonality position computed tomography (CT) image and method for forecasting lung cancers

A technology of CT image and extraction method, which is applied in the field of medical imaging diagnosis and can solve different problems

Inactive Publication Date: 2012-07-04
CAPITAL UNIVERSITY OF MEDICAL SCIENCES
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Problems solved by technology

[0008] The difference between benign and malignant pulmonary nodules is not only different in the texture of CT images, but also related to many risk factors. However, how to combine the Curvelet texture of pulmonary nodules on three orth...

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  • Method for extracting texture based on lung nodules three orthogonality position computed tomography (CT) image and method for forecasting lung cancers
  • Method for extracting texture based on lung nodules three orthogonality position computed tomography (CT) image and method for forecasting lung cancers
  • Method for extracting texture based on lung nodules three orthogonality position computed tomography (CT) image and method for forecasting lung cancers

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Embodiment Construction

[0013] The present invention provides a method for extracting the texture of CT images based on three orthogonal positions of pulmonary nodules, comprising the following steps: a. establishing a three-orthogonal position CT image system of pulmonary nodules; b. extracting pulmonary nodules through the discrete Curvelet transform method Three orthogonal texture feature parameters.

[0014] As a further improvement of the present invention, the three orthogonal views are: coronal view, sagittal view and axial view.

[0015] As a further improvement of the present invention, the texture feature parameter is an edge texture feature parameter.

[0016] As a further improvement of the present invention, the texture feature parameters are spatial domain, frequency domain and / or geometric features.

[0017] As a further improvement of the present invention, the spatial domain, frequency domain and / or geometric features are high frequency ratio, entropy, energy, mean, standard deviati...

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Abstract

The invention discloses a method for extracting texture based on a lung nodules three orthogonality position computed tomography (CT) image, which includes: a building a lung nodules three orthogonality position CT image system; and b extracting lung nodules three orthogonality position texture characteristic parameters through a disperse Curvelet transformation method. The invention further discloses a method for forecasting lung cancers, which includes: a extracting lung CT image texture characteristics; b extracting three orthogonality position CT image and video signs; and c building a forecasting model based on multi-dimensional characteristic parameters including lung nodules three orthogonality position CT image texture characteristics and video signs through a Gradient Boosting algorithm. The method for extracting texture based on lung nodules three orthogonality position CT image and the method for forecasting lung cancer can be used for early diagnosis of pulmonary nodules.

Description

technical field [0001] The invention relates to a medical image diagnosis technology, in particular to a method for extracting a texture of a CT image based on three orthogonal positions of a pulmonary nodule and a method for predicting lung cancer. Background technique [0002] In recent years, lung cancer has always ranked first in cancer mortality in most countries in the world (SR Kim, et al. al.2010)[2], and in the next 30 years, lung cancer will still be the main cause of death in China (JW Wang, et al.2005)[3]. Despite the continuous development of science and technology, the prognosis of lung cancer is still poor, and the 5-year survival rate in most countries is only 10% (G Mountzios, et al. 2010) [4]. However, lung cancer patients can be diagnosed at an early stage, and the 10-year survival rate can reach 92% (N Seki, et al. 2010) [5]. However, more than 80% of the patients are in the middle and advanced stage when they are diagnosed. Therefore, the prevention a...

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Application Information

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IPC IPC(8): G06T7/00A61B6/03
Inventor 郭秀花孙涛刘韫宁吴海丰王嵬
Owner CAPITAL UNIVERSITY OF MEDICAL SCIENCES
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