Automated Methods for the Decision Support of Cervical Cancer Screening Using Digital Colposcopies

• Type: Article in International Scientific Journal
• Date: 2018

Authors

Kelwin Fernandes (Author) Other; Jaime S. Cardoso (Author) FEUP; Jessica Fernandes (Author) Other

Journal

Title: IEEE Access

Vol. 6

Pages: 33910-33927

ISSN: 2169-3536

Publisher: IEEE

Indexing

ISI Web of Knowledge - 34 Citations

Scopus - 49 Citations

INSPEC

Other information

Authenticus ID: P-00P-0TZ

DOI: 10.1109/access.2018.2839338

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 18