Convolutional neural network-based fungal keratitis detection method and system

A technology of convolutional neural network and fungal keratitis, which is applied in the field of medical image processing, can solve the problems of long culture time of fungi, high error rate, and poor effect, and achieve the effect of fast recognition speed and improved recognition rate

Inactive Publication Date: 2019-05-31
武汉爱尔眼科汉口医院有限公司
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Problems solved by technology

[0005] At present, there are many methods for the examination of fungal keratitis. The positive rate of smear examination is low, the culture time of fungi is long, and the examination of

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  • Convolutional neural network-based fungal keratitis detection method and system
  • Convolutional neural network-based fungal keratitis detection method and system
  • Convolutional neural network-based fungal keratitis detection method and system

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Embodiment Construction

[0042] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.

[0043] see figure 1 As shown, the embodiment of the present invention provides a method for detecting fungal keratitis based on a convolutional neural network. This method realizes automatic matching, identification and classification of samples to be detected by establishing a convolutional neural network model. Compared with The existing technology not only improves the recognition rate, but also has a fast recognition speed and saves time and effort. After replacing the training sample set, this method can be applied to other application scenarios except the identification of fungal keratitis.

[0044] The detection method comprises the steps of:

[0045] S1: see figure 2 As shown, the training sample set was collected, and the training sample was imaged with a confocal laser microscope. According to whether there is fungal hyphae on th...

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Abstract

The invention discloses a convolutional neural network-based fungal keratitis detection method and system, and the method comprises the following steps: collecting a training sample set, and dividingthe training sample set into a fungal mycelium picture set and a fungal mycelium-free picture set; preprocessing the training sample set; constructing a convolutional neural network; Inputting the preprocessed training sample set as training data into the convolutional neural network, and performing iterative training through a gradient descent method and a back propagation algorithm to obtain a detection model with a fungal mycelium recognition function; and detecting a to-be-detected sample by using the detection model, and outputting a detection result. The detection method provided by theinvention has the advantages of high recognition speed and high recognition rate.

Description

technical field [0001] The invention relates to the technical field of medical image processing, in particular to a method and system for detecting fungal keratitis based on a convolutional neural network. Background technique [0002] Convolutional Neural Network (CNN) is an artificial neural network structure that has been developed in recent years and has attracted widespread attention. Convolutional neural network has good fault tolerance, parallel processing ability and self-learning ability, and has achieved good results in speech recognition and face recognition. Currently the most widely used is in computer image recognition. [0003] Fungal keratitis is an infectious corneal disease caused by pathogenic fungi with a high rate of blindness. Fungal keratitis has a slow onset and a long course, which can last for 2 to 3 months, and corneal ulcers often appear within a few days of onset. In our country, most of the patients are peasants. [0004] If fungal keratitis...

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Application Information

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IPC IPC(8): G06T7/00G16H50/20
Inventor 曾庆延孙涛刘慧林吴雨昊孙夫熊谌丹陈敏何玉枚王浩宇乔晨
Owner 武汉爱尔眼科汉口医院有限公司
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