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

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...

Descripció completa

Dades bibliogràfiques
Autors principals: Zhen Li, Chu-Mei Zeng, Yan-Gang Dong, Ying Cao, Li-Yao Yu, Hui-Ying Liu, Xun Tian, Rui Tian, Chao-Yue Zhong, Ting-Ting Zhao, Jia-Shuo Liu, Ye Chen, Li-Fang Li, Zhe-Ying Huang, Yu-Yan Wang, Zheng Hu, Jingjing Zhang, Jiu-Xing Liang, Ping Zhou, Yi-Qin Lu
Format: Article
Idioma:English
Publicat: Elsevier 2023-11-01
Col·lecció:Heliyon
Matèries:
HSIL
Colposcopy
Diagnosis
Segmentation
Artificial intelligence
Accés en línia:http://www.sciencedirect.com/science/article/pii/S2405844023082518

Internet

http://www.sciencedirect.com/science/article/pii/S2405844023082518

Ítems similars