Paper Info
Title
Automated Methods for the Decision Support of Cervical Cancer Screening Using Digital Colposcopies.
Abstract
Cervical cancer remains a significant cause of mortality in low-income countries. However, it can often be cured by removing the affected tissues when detected in early stages. Therefore, it is relevant to provide universal and efficient access to cervical screening programs, being digital colposcopy an inexpensive technique with high potential of scalability. The development of computer-aided diagnosis systems for the automated processing of digital colposcopies has gained the attention of the computer vision and machine learning communities in the last decade, giving origin to a wide diversity of tasks and computational solutions. However, there is a lack of a unified framework to discuss the main tasks and to assess their performance. Thus, in this paper, we studied the core research lines surrounding the automated analysis of digital colposcopies and built a topology of problems and techniques, including their key properties, advantages, and limitations. Also, we discussed the open challenges in the area and released a database that serves as a common basis to evaluate such systems.
Year
DOI
Venue
2018
10.1109/ACCESS.2018.2839338
IEEE ACCESS
Keywords
Field
DocType
Cervical cancer,digital colposcopy,computer aided diagnosis,machine learning,computer vision
Cervical cancer,Cervical screening,Task analysis,Computer science,Decision support system,Artificial intelligence,Machine learning,Scalability,Distributed computing,Colposcopy
Journal
Volume
ISSN
Citations 
6
2169-3536
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Kelwin Fernandes1367.71
Jaime S. Cardoso254368.74
Jessica Fernandes300.34