PCNN automatic segmentation method for microscopic image of traditional Chinese medicine

A microscopic image and automatic segmentation technology, applied in the field of biomedical information processing, can solve problems such as many parameters, no usable information, complex models, etc.

Inactive Publication Date: 2016-10-12
TIANSHUI NORMAL UNIV
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Problems solved by technology

[0007] The purpose of the present invention is to provide a PCNN automatic segmentation method for microscopic images of Chinese herbal medicines, aiming at solving the problem that the traditional PCNN model threshold attenuation changes repeatedly, which cannot

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  • PCNN automatic segmentation method for microscopic image of traditional Chinese medicine
  • PCNN automatic segmentation method for microscopic image of traditional Chinese medicine
  • PCNN automatic segmentation method for microscopic image of traditional Chinese medicine

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[0076] In order to further understand the content, features and effects of the present invention, the following examples are given, and detailed descriptions are given below with reference to the accompanying drawings.

[0077] see figure 1 and figure 2 :

[0078] Microscopic image acquisition preprocessing and database construction of Chinese herbal medicines:

[0079] (1) According to the pharmacopoeia, hundreds of medicinal plants such as angelica, codonopsis, licorice, rhubarb, astragalus, lily, ephedra, bupleurum, isatidis, fennel, safflower, gastrodia elata, and fritillaria, distributed in different regions of Gansu province, are to be recorded As the original object of the study, samples of authentic medicinal materials (or medicinal herb pollen samples) were collected from the growing areas in different medicinal materials growing seasons, and high-resolution digital cameras were used to obtain images of the morphology of traditional Chinese medicines.

[0080] (2)...

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Abstract

The invention discloses a PCNN automatic segmentation method for a microscopic image of a traditional Chinese medicine. The PCNN automatic segmentation method comprises the steps of respectively establishing a CNN automatic binary image dividing algorithm which utilizes cross entropy segmentation criteria; establishing a traditional Chinese medicine microscopic image PCNN multi-value image automatic segmentation algorithm which utilizes maximizing mutual information as a segmentation object and utilizes mutual information entropy difference as a classification criteria, designing a vector pulse coupling neural network model, and realizing automatic segmentation on the microscopic color image of the traditional Chinese medicine through utilizing an index entropy criterion as a segmentation criteria; and establishing a traditional Chinese medicine microscopic image dividing algorithm in a multichannel or three-dimensional PCNN through utilizing a fuzzy index entropy as an optimized segmentation criterion. The PCNN automatic segmentation method has advantages of further improving objectivity, accuracy, repeatability and intelligent degree in quality evaluation of the traditional Chinese medicine, and providing a new approach for modernization of testing and analysis of the traditional Chinese medicine.

Description

technical field [0001] The invention belongs to the field of biomedical information processing, in particular to a PCNN automatic segmentation method for microscopic images of Chinese herbal medicines. Background technique [0002] Pulse-coupled neural network (PCNN) is proposed based on the synchronous pulse emission phenomenon in the visual cortex of mammals such as cats and monkeys. It has a good biological background. The model has dynamic variable threshold, nonlinear modulation coupling, synchronous pulse The characteristics of pulse emission and space-time summation make PCNN show great advantages in signal processing applications, especially in image processing applications. However, the traditional PCNN model still has the following theoretical and technical shortcomings: [0003] (1) In terms of nonlinear modulation coupling and threshold exponential decay, the threshold decay of this model is repeatedly changed. This threshold change cannot well meet the nonlinea...

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Application Information

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IPC IPC(8): G06T7/00G06N3/04G06T5/00G06T7/40G06T7/60G06K9/48
CPCG06N3/049G06T5/002G06T2207/20064G06T2207/20084G06T2207/10056G06V10/46
Inventor 刘勍杨红平赵玉祥杨筱平马小姝张利军韩双旺
Owner TIANSHUI NORMAL UNIV
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