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Biochip analysis method based on active contour model and cell neural network

An active contour model, biochip technology, applied in neural learning methods, biological neural network models, image analysis, etc., can solve the problems of low efficiency, difficult to improve accuracy, and high subjective dependence of operators.

Active Publication Date: 2013-08-07
CENT SOUTH UNIV
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Problems solved by technology

For the characteristics of high density and large amount of information of biochips, the manual assisted identification method is inefficient, has a large subjective dependence on the operator, and it is difficult to improve the accuracy

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  • Biochip analysis method based on active contour model and cell neural network
  • Biochip analysis method based on active contour model and cell neural network
  • Biochip analysis method based on active contour model and cell neural network

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Embodiment Construction

[0268] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with specific implementation examples and with reference to the accompanying drawings.

[0269] attached figure 1 For the technical solution of the present invention, C#2.0 programming is used to complete the entire process, and the present invention is described in more detail with reference to the accompanying drawings.

[0270] (1) Use the improved Hough transform to correct the tilt of the rectangular sample image

[0271] It is known that the inclination angle of a rectangular sample chip image is 2.15° (counterclockwise as the positive direction of rotation), see the attached figure 2 . Image preprocessing such as filter noise reduction, grayscale enhancement, etc. is performed on the input image. The Otsu algorithm is used to binarize the preprocessed image, and then a morpholog...

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Abstract

The invention discloses a biochip analysis method based on an active contour model and a cell neural network. The method comprises the following steps that improved Hough transformation is adopted to perform slant correction on a rectangular sampling point, and improved Radon transformation is adopted for a circular sampling point; initial positioning is performed on the sampling points by using a projection method, and an optimized network is generated; then the network is adaptively adjusted on the basis of neighborhood search, and secondary precise positioning is performed on the sampling points; the active contour model is optimized by using a greedy algorithm, and a CNN (Cable News Network) is utilized to classify the sampling points in accordance with signal strength; Multiple snakes are combined with the CNN, the CNN first learns about the convergence behavior of the sampling point snake with a strong signal and then guides the convergence of the sampling point snake with a weak signal, and finally, reasonable partition of the sampling points is realized; and signal data of microarray sampling points is extracted and output. By using the method, the problems of slant correction of a biochip image, difficulty in partition of sampling points with irregular shapes and sampling points with weak signals and the like are solved, automatic identification of biochip sampling points is realized, and the method is suitable for quick analysis of large-scale biochip sampling points.

Description

technical field [0001] The invention belongs to the technical field of biochips, in particular to a biochip analysis method based on an active contour model and a cellular neural network, which can be applied to the processing, automatic identification and analysis of biochip scanning images. Background technique [0002] Biochip is a microfluidic analysis unit and system constructed on the surface of a solid chip through planar microfabrication technology to achieve accurate, rapid, and large-scale detection of cells, proteins, nucleic acids, and other biological components. Throughput, parallel automatic processing and other advantages. Biochip technology makes full use of the achievements of biological science, informatics and other disciplines, and has been widely used in medicine, life science, environmental science and other related fields. [0003] Spot recognition of biochip is the key technology of biochip detection system. Biochips integrate a large number of dot...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06N3/08
Inventor 刘正春吴灶全陈熹彭程柳建新
Owner CENT SOUTH UNIV
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