Classification and diagnosis of cervical lesions based on colposcopy images using deep fully convolutional networks: A man-machine comparison cohort study

Classification and diagnosis of cervical lesions based on colposcopy images using deep fully convolutional networks: A man-machine comparison cohort study

Colposcopy is an important technique in the diagnosis of cervical cancer. The development of computer-aided diagnosis methods can mitigate the shortage of colposcopists and improve the accuracy and efficiency of colposcopy examinations in China. This study proposes the Dense-U-Net model for colposco...

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Bibliographic Details
Main Authors: Binhua Dong, Huifeng Xue, Ye Li, Ping Li, Jiancui Chen, Tao Zhang, Lihua Chen, Diling Pan, Peizhong Liu, Pengming Sun
Format: Article
Language:English
Published: KeAi Communications Co. Ltd. 2025-01-01
Series:Fundamental Research
Subjects:
Cervical lesions
Dense-U-Net
Colposcopic image
Lesion segmentation
Auxiliary diagnosis
Online Access:http://www.sciencedirect.com/science/article/pii/S2667325822004319
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http://www.sciencedirect.com/science/article/pii/S2667325822004319

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