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Optical microscope automatic focusing method based on machine learning

An optical microscope and machine learning technology, applied in the field of medical image processing, which can solve problems such as poor versatility and slow speed

Active Publication Date: 2019-03-22
湖南品信生物工程有限公司
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Problems solved by technology

A large number of search strategies such as hill climbing method, dichotomy method, Fibonacci search method, fuzzy control search method, adaptive step size method, function curve fitting method, discrete difference equation prediction method, etc. have been used to automatically focus, to a certain extent Improves the speed and precision of focusing, but has the disadvantages of poor versatility and slow speed, and is not suitable for automatic focusing of microscopes with high precision

Method used

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  • Optical microscope automatic focusing method based on machine learning
  • Optical microscope automatic focusing method based on machine learning
  • Optical microscope automatic focusing method based on machine learning

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Embodiment Construction

[0112] In order to make the object, technical solution and beneficial technical effect of the present invention clearer, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the embodiments described in this specification are only for explaining the present invention, not for limiting the present invention, and the specific parameter settings of the embodiments can be selected according to local conditions and have no substantial impact on the results.

[0113] Step 1: If figure 2 As shown, 200 raw images were collected along the Z-axis of the optical microscope I i (x, y), and converted to a grayscale image f i (x, y), where i = {1, 2, ..., p};

[0114] Step 2: Repeat step 1, each time recorded as a group (such as figure 2 shown), collecting 20 sets of data and a total of N pictures;

[0115] Step 3: Calculate 48 original features for each image and 96 combined features and respectively re...

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Abstract

The invention provides an optical microscope automatic focusing method based on machine learning, and belongs to the technical field of medical image processing. The method comprises the steps that firstly, images collected by an optical microscope and grouped are represented by designed original features and combined features, and the sequence difference value of a picture and the most clear picture in the group serves as the label of the picture; then the importance of the original features and the combined features is calculated by adopting a random forest composed of regression trees, andthe features with high importance are screened out through multiple times of iteration with the cooperation of set threshold value; data is divided into a training set and a test set by using a leave-one-out method and the screened features to train the gradient boosted regression trees, and finally automatic focusing is carried out on a strong regression device obtained through iterative training.

Description

technical field [0001] The invention belongs to the technical field of medical image processing, and relates to an automatic focusing method of an optical microscope based on machine learning. technical background [0002] The traditional method of manual image reading has brought heavy labor to pathologists, and reading images for a long time with high concentration is prone to visual fatigue, which greatly increases the probability of misdiagnosis. In recent years, with the development of automation and intelligence of microscopes, automatic reading technology has begun to appear and develop rapidly. The automatic film reading technology of the microscope uses the automatic focusing algorithm to capture clear images under the microscope, and then conducts subsequent pathological analysis. As the first step of the automatic film reading technology, the automatic focusing algorithm of the microscope greatly affects the subsequent pathological analysis process, and its speed ...

Claims

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Application Information

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IPC IPC(8): G02B21/24
CPCG02B21/244
Inventor 梁毅雄
Owner 湖南品信生物工程有限公司
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