José M. Franco-Valiente; César Suárez-Ortega

International Journal of Image Mining (IJIM), Vol. 1, No. 2/3, 2015



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.