Cervical image lesion area segmentation device and method based on classification prior

The invention discloses a cervical image lesion area segmentation device and method based on classification prior, and the device comprises an image collection device which is used for collecting 3%-5% of the cervical image processed by the acetic acid solution. The processor comprises a cervix imag...

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Hauptverfasser: CHEN TINGTING, WANG WENZHE, YUAN CHUNNYU, WU FULI, LYU WEIGUO, LEI BIWEN, MA XINJUN, WU JIAN, LIU XUECHEN, WANG XINYU, LU YIFEI, YAO YELI
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creator CHEN TINGTING
WANG WENZHE
YUAN CHUNNYU
WU FULI
LYU WEIGUO
LEI BIWEN
MA XINJUN
WU JIAN
LIU XUECHEN
WANG XINYU
LU YIFEI
YAO YELI
description The invention discloses a cervical image lesion area segmentation device and method based on classification prior, and the device comprises an image collection device which is used for collecting 3%-5% of the cervical image processed by the acetic acid solution. The processor comprises a cervix image preprocessing module and a processing module, and the processing module comprises a segmentation network model composed of a U-shaped network based on residual error connection, an image level classifier and a pixel level classifier and is used for outputting and predicting the position of a lesion area on the cervix image; The memory is used for storing parameters of the segmented network model in the processor; and the display device is used for displaying the predicted lesion area positionoutput by the processor. By means of the method and device, high-accuracy biopsy focus position candidate areas can be provided for doctors, and the biopsy positive detection rate is increased. 本发明公开了种基于分类先验的宫颈图像病变区域分割装置和方法,其
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subjects CALCULATING
COMPUTING
COUNTING
DIAGNOSIS
HANDLING RECORD CARRIERS
HUMAN NECESSITIES
HYGIENE
IDENTIFICATION
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
MEDICAL OR VETERINARY SCIENCE
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
SURGERY
title Cervical image lesion area segmentation device and method based on classification prior
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