A segmentation model to detect cevical lesions based on machine learning of colposcopic images

BACKGROUND: Semantic segmentation is crucial in medical image diagnosis. Traditional deep convolutional neural networks excel in image classification and object detection but fall short in segmentation tasks. Enhancing the accuracy and efficiency of detecting high-level cervical lesions and invasive...

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Detalles Bibliográficos
Autores principales: Li, Zhen, Zeng, Chu-Mei, Dong, Yan-Gang, Cao, Ying, Yu, Li-Yao, Liu, Hui-Ying, Tian, Xun, Tian, Rui, Zhong, Chao-Yue, Zhao, Ting-Ting, Liu, Jia-Shuo, Chen, Ye, Li, Li-Fang, Huang, Zhe-Ying, Wang, Yu-Yan, Hu, Zheng, Zhang, Jingjing, Liang, Jiu-Xing, Zhou, Ping, Lu, Yi-Qin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623278/
https://www.ncbi.nlm.nih.gov/pubmed/37928028
http://dx.doi.org/10.1016/j.heliyon.2023.e21043

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623278/
https://www.ncbi.nlm.nih.gov/pubmed/37928028
http://dx.doi.org/10.1016/j.heliyon.2023.e21043

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