Classification of cervical cancer from Pap smear images: : a convolutional neural network approach
Abstract
Recommendations
Automated classification of Pap smear images to detect cervical dysplasia
An automated Pap smear classifier is proposed to detect cervical dysplasia.Study performed on both cell as well as smear level indigenous real images collected from two diagnostic centers.Analysis is being performed on shape, texture and color features ...
Cervical Cancer Detection and Classification from Pap Smear Images
ICBSP '19: Proceedings of the 2019 4th International Conference on Biomedical Imaging, Signal ProcessingIn this paper, we propose a framework for detection and classification of cervical cancer from pap smear images. Early detection and accurate diagnosis of cervical cancer can reduce the death rate of cervical cancer patients. Pap smear or pap test is ...
Single and Clustered Cervical Cell Classification with Ensemble and Deep Learning Methods
AbstractCervical cancer if detected early has an upward of 89% survival rate. The leading tool in identifying cervical cancer in its infancy is the Papanicolaou (Pap smear) test, which since its introduction dropped cervical cancer related deaths by 60%. ...
Comments
Information & Contributors
Information
Published In
Publisher
Inderscience Publishers
Geneva 15, Switzerland
Publication History
Author Tags
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Other Metrics
Citations
View Options
View options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in