Classifying Papanicolaou cervical smears through a cell merger approach by deep learning technique-Reference-Cited by-同舟云学术

Classifying Papanicolaou cervical smears through a cell merger approach by deep learning technique

Published:2020-12 Issue: Volume:160 Page:113707
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Martínez-Más José,Bueno-Crespo Andrés,Martínez-España Raquel,Remezal-Solano Manuel,Ortiz-González Ana,Ortiz-Reina Sebastián,Martínez-Cendán Juan-Pedro

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference41 articles.

1. Medical image retrieval with compact binary codes generated in frequency domain using highly reactive convolutional features;Ahmad;Journal of Medical Systems,2018

2. Comparison of manual and automated methods of liquid-based cytology;Alves;Acta Cytologica,2004

3. European guidelines for quality assurance in cervical cancer screening. Summary document;Arbyn;Annals of Oncology,2010

4. Liquid compared with conventional cervical cytology: A systematic review and meta-analysis;Arbyn;Obstetrics & Gynecology,2008

5. Virologic versus cytologic triage of women with equivocal Pap smears: A meta-analysis of the accuracy to detect high-grade intraepithelial neoplasia;Arbyn;Journal of the National Cancer Institute,2004

Cited by 24 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Transformative Advances in Cervical Cancer Diagnosis Leveraging Colposcopy Imaging with ViT;2024 International Conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence (RAEEUCCI);2024-04-17

2. A lightweight xAI approach to cervical cancer classification;Medical & Biological Engineering & Computing;2024-03-20

3. A two-stage approach solo_GAN for overlapping cervical cell segmentation based on single-cell identification and boundary generation;Applied Intelligence;2024-03

4. Diagnosis of Cervical Cancer Using a Deep Learning Explainable Fusion Model;Lecture Notes in Computer Science;2024

5. Medical image compression and restoration using a hybrid neural network combining Huffman and meta-heuristic techniques;2023-12-28