A Two-Stream Decision Fusion Network for Cervical Pap-smear Image Classification Tasks DOI
Tianjin Yang, Hexuan Hu, Xing Li

et al.

Tissue and Cell, Journal Year: 2024, Volume and Issue: 90, P. 102505 - 102505

Published: July 31, 2024

Language: Английский

CTCNet: a fine-grained classification network for fluorescence images of circulating tumor cells DOI
Juntao Wu, Han Wang, Yuman Nie

et al.

Medical & Biological Engineering & Computing, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 22, 2025

Language: Английский

Citations

0
Convolutional Block Attention Module and Parallel Branch Architectures for Cervical Cell Classification DOI Open Access
Zafer Cömert,

Ferat Efil,

Muammer Türkoğlu

et al.

International Journal of Imaging Systems and Technology, Journal Year: 2025, Volume and Issue: 35(2)

Published: Feb. 18, 2025

ABSTRACT Cervical cancer persists as a significant global health concern, underscoring the vital importance of early detection for effective treatment and enhanced patient outcomes. While traditional Pap smear tests remain an invaluable diagnostic tool, they are inherently time‐consuming susceptible to human error. This study introduces innovative approach that employs convolutional neural networks (CNN) enhance accuracy efficiency cervical cell classification. The proposed model incorporates Convolutional Block Attention Module (CBAM) parallel branch architectures, which facilitate feature extraction by focusing on crucial spatial channel information. process entails identification utilization most pertinent elements within image purpose was meticulously assessed SIPaKMeD dataset, attaining exceptional degree (92.82%), surpassed performance CNN models. incorporation sophisticated attention mechanisms enables not only accurately classify images but also interpretability emphasizing regions images. highlights transformative potential cutting‐edge deep learning techniques in medical analysis, particularly screening, providing powerful tool support pathologists accurate diagnosis. Future work will explore additional extend application this architecture other imaging tasks, further enhancing its clinical utility impact

Language: Английский

Citations

0
Performance of artificial intelligence for diagnosing cervical intraepithelial neoplasia and cervical cancer: a systematic review and meta-analysis DOI Creative Commons
Lei Liu, Jiangang Liu, Qing Su

et al.

EClinicalMedicine, Journal Year: 2024, Volume and Issue: 80, P. 102992 - 102992

Published: Dec. 28, 2024

Language: Английский

Citations

1
A Two-Stream Decision Fusion Network for Cervical Pap-smear Image Classification Tasks DOI
Tianjin Yang, Hexuan Hu, Xing Li

et al.

Tissue and Cell, Journal Year: 2024, Volume and Issue: 90, P. 102505 - 102505

Published: July 31, 2024

Language: Английский

Citations

0