ALOE platform: an overview of a service-oriented architecture for research in breast cancer diagnosis supported by e-infrastructures. (2015)

• Record Type: Journal Article
• Authors: Franco-Valiente, José M.; Suárez-Ortega, César
• Is Part Of: International journal of image mining. Volume 1:Number 2/3(2015)
• Page Start: 245
• Page End: 260
• Publication Date: 2015
• Subjects: e-learning -- electronic learning -- online learning -- virtual infrastructure -- breast cancer -- digital repositories -- computer aided diagnosis -- service-oriented architecture -- SOA -- cancer diagnosis -- early detection -- radiologist training -- radiology -- mammography -- medical images -- mammograms; Image processing -- Periodicals; Data mining -- Periodicals; 006.42
• Languages: English
• ISSNs: 2055-6039

Abstract

This article presents an overview of the ALOE platform. ALOE provides a service-oriented architecture aimed at the research in the early detection of breast cancer diagnosis. The development of the ALOE platform is carried out by collaboration among CETA-CIEMAT, INEGI, FMUP-HSJ and UA. ALOE supports two research lines in breast cancer diagnosis: the development of well performing computer aided diagnosis (CAD) systems and the development of new tools-based on e-learning techniques to improve radiologists training. All ALOE modules are designed to work as a whole system but can be used individually in other systems and expose RESTful interfaces to be exploited by third party systems. ALOE components make use of e-Infrastructure resources to accomplish their tasks. The final objective of this work is to provide a reference platform for researchers, specialists, and students in breast cancer diagnosis.