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Automatic identification system for urinary sediment visible components based on support vector machine

An automatic identification system and support vector machine technology, applied in the field of medical devices, can solve the problems of unreliable quantitative conclusions and heavy workload

Inactive Publication Date: 2010-12-01
UNIV OF SHANGHAI FOR SCI & TECH
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Problems solved by technology

This method has a certain degree of subjectivity and arbitrariness, and the workload is large and the quantitative conclusion is not very reliable.

Method used

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  • Automatic identification system for urinary sediment visible components based on support vector machine
  • Automatic identification system for urinary sediment visible components based on support vector machine
  • Automatic identification system for urinary sediment visible components based on support vector machine

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Embodiment Construction

[0011] see figure 1 , the automatic identification system of urinary sediment formed components based on support vector machine of the present invention may at least include: an image acquisition module, an image database, an initial labeling module, an image processing module, a relabeling module, a support vector machine forming module, and a urine sediment organic component Form a component identification module, etc.

[0012] The image collection module is used to collect multiple images of urine samples under a microscope and images of urine samples to be identified. Usually, the number of urine sample images is as large as possible, so as to include normal urine and various common abnormal urine.

[0013] The image database is used to store the collected urine sample images and the urine sample images to be identified.

[0014] The primary labeling module is used to provide a primary labeling interface, so that experts can label each collected urine sample image as an ...

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Abstract

The invention provides an automatic identification system for urinary sediment visible components based on a support vector machine, which comprises an image acquisition module, an image data base, a primary labeling module, an image processing module, a secondary labeling module, a support vector machine forming module, a urinary sediment visible component identification module and the like, and organically combines three major procedures of image segmentation and processing, support vector machine training and urinary sediment visible component identification together to form a systemic and complete technical frame for the training and the automatic identification of the urinary sediment visible components based on the SVM method. The system can be used in the segmentation, training and automatic identification processes of the urinary sediment visible components in the view field of a microscope, and provides a basic solution for the implementation of a computer-aided detection system for routine urine examination based on a microscope.

Description

technical field [0001] The technology of the invention relates to an automatic identification system for formed components of urine sediment based on a support vector machine, and belongs to the technical field of medical devices. Background technique [0002] Urinary sediment formed component analysis is a relatively important item in clinical routine inspection work, and it is also one of the important means for doctors to judge urinary system diseases at present, and has extremely important value in the diagnosis of kidney and urinary tract diseases. [0003] The routine detection method for the formed components of urine sediment is to observe the pictures under a microscope or take pictures with a camera device and then manually identify them. This method has a certain degree of subjectivity and arbitrariness, a large workload and the quantitative conclusion is not very reliable. With the application and development of computer technology, people have gradually develop...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N35/00G06K9/60G06K9/62
Inventor 陈兆学樊晓燕郑建立
Owner UNIV OF SHANGHAI FOR SCI & TECH
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