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Automatic random-walk CT lung parenchyma image segmentation method based on prior information

A technology of random walk and prior information, applied in the field of image processing, can solve the problem that the segmentation of lung tissue images is affected by the number and position of seed points

Inactive Publication Date: 2015-09-23
XIAN UNIV OF TECH
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Problems solved by technology

[0005] The purpose of the present invention is to provide a random walk CT lung tissue image automatic segmentation method based on prior information. Technical issues that have a great influence on the number and position of seed points

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  • Automatic random-walk CT lung parenchyma image segmentation method based on prior information
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  • Automatic random-walk CT lung parenchyma image segmentation method based on prior information

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Embodiment Construction

[0081] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0082] The random walk CT lung tissue image automatic segmentation method based on the prior information of the present invention, such as figure 1 shown, including the following steps:

[0083] Step 1, input the original CT image (such as figure 2 shown), the input CT image is subjected to binary discrete wavelet transform to obtain image M;

[0084] Step 1.1: In the two-dimensional case, select three wavelet functions in different spatial directions for binary discrete wavelet transform, respectively, the wavelet function ψ in the horizontal direction 1 (x, y), wavelet function ψ in the vertical direction 2 (x, y), wavelet function ψ in the diagonal direction 3 (x, y), the wavelet transform of CT image f(x, y) is:

[0085] W n = f ( j ,...

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Abstract

The invention discloses an automatic random-walk CT lung parenchyma image segmentation method based on prior information. The method comprises the following steps that an original CT image is input, and binary discrete wavelet transformation is carried out on the input CT image to obtain an image M; a chest area is extracted from the image M in an entropy based superpixel method, and then processed to obtain an image T; the amount and position of seed points of the image T are obtained by utilizing the prior information guided by anatomy knowledge, and random-walk segmentation is carried out on the obtained seed points to obtain an initial parenchyma contour of the lung; and local mis-segmented areas of the initial parenchyma contour of the lung are repaired in a curvature rectification algorithm. Thus, the method of the invention can be used to solve the technical problem that in the present random-walk technology, the segmented lung parenchyma image is greatly influenced by the amount and positions of the seed points when the seed points are selected by manual interaction.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a random walk CT lung tissue image automatic segmentation method based on prior information. Background technique [0002] Lung tissue segmentation is the first key technical step that must be performed in the detection of lung diseases using computer-aided diagnosis and treatment systems, which directly affects the subsequent detection and analysis results. Studies have shown that 5%-7% of missed lung diseases are related to inaccurate segmentation of lung tissue. Computed tomography (Computer Tomography, CT) is one of the more common techniques in clinical computer-assisted detection of lung diseases. However, due to the diversity of biological tissues and the inherent uncertainty of imaging equipment, the slices obtained by CT cross-sectional scanning There is a certain degree of fuzziness in the image, which makes the computer automatic segmentation technology face a ...

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Application Information

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IPC IPC(8): G06T7/00
CPCG06T7/11G06T2207/30061
Inventor 石争浩司春娇
Owner XIAN UNIV OF TECH
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