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Cell image segmentation method based on U-Net network

An image segmentation and network technology, applied in image analysis, image enhancement, image data processing, etc., can solve problems such as deficiencies, and achieve the effect of reducing difficulty and improving accuracy

Inactive Publication Date: 2020-09-08
HARBIN UNIV OF SCI & TECH
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Problems solved by technology

[0003] In order to solve the problem that the traditional cell image segmentation algorithm and the cell image segmentation algorithm based on deep learning are insufficient; the purpose of the present invention is to provide a cell image segmentation method based on U-Net network

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Embodiment Construction

[0033] In order to make the object, technical solution and advantages of the present invention clearer, the present invention is described below through specific embodiments shown in the accompanying drawings. It should be understood, however, that these descriptions are exemplary only and are not intended to limit the scope of the present invention. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concept of the present invention.

[0034] Here, it should also be noted that, in order to avoid obscuring the present invention due to unnecessary details, only the structures and / or processing steps closely related to the solution according to the present invention are shown in the drawings, and the related Other details are not relevant to the invention.

[0035] like figure 1 Shown, this specific embodiment adopts following technical scheme: its method is as follows:

[0036] Step 1: Imag...

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Abstract

The invention discloses a cell image segmentation method based on a U-Net network, and relates to the technical field of cell image segmentation. The method comprises the following steps: step 1, an image preprocessing method: 1.1, contrast image enhancement; 1.2, performing Gaussian filtering; 2, a cervical cell segmentation method based on U-Net: 2.1, performing preliminary segmentation by usinga U-Net network; 2.2, adding a hole convolution structure and a residual structure into the U-Net network; 2.3, detecting the edges of the cells by using a clustering detection method; according to the method, a deep learning network is mainly used for segmenting a cervical cell image, and a clustering method is used for auxiliary segmentation; not only can the design difficulty of the classifierbe reduced, but also the accuracy of cancer cell diagnosis can be remarkably improved.

Description

technical field [0001] The invention belongs to the technical field of cell image segmentation, and in particular relates to a cell image segmentation method based on a U-Net network. Background technique [0002] As a new field in machine learning research, deep learning has made great achievements in image recognition and object detection in recent years, and these achievements are undoubtedly due to the use of convolutional neural networks (CNNs). Naturally, deep learning has also been applied in research on cancer detection. Currently, there are two directions for cancer detection based on deep learning: one direction is to perform image segmentation first and then perform cancer detection like the traditional segmentation direction; the other direction is to skip the image segmentation process and directly use cell images for cancer detection. detection. In the direction of segmentation first and then detection, current segmentation methods are mainly based on two neu...

Claims

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Application Information

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IPC IPC(8): G06T7/13G06T7/155G06T7/194G06N3/04G06N3/08G06T5/00
CPCG06T7/13G06T7/155G06T7/194G06N3/084G06T2207/30024G06T2207/20081G06T2207/20084G06T2207/30096G06N3/045G06T5/90G06T5/70
Inventor 黄金杰狄爱景
Owner HARBIN UNIV OF SCI & TECH
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