Autor

Raul Ramos Pollán, Jose Miguel Franco, Jorge Sevilla, Naimy González de Posada, Noel Pérez Pérez, Mario Augusto Pires Vaz, Joana Loureiro, Isabel Ramos, Miguel Ángel Guevara López.

Evento

4rd Iberian Grid Infrastructure Conference
Lugar: Braga (Portugal)
Fecha: 24-27 Mayo 2010
Tipo de publicación:Oral

Abstract

This paper presents a novel Grid based software platform to store and manage large mammography digital image repositories (MDIR) including associated patient information (clinical history, biopsies, etc.), a mammography image workstation for analysis and diagnosis (MIWAD) and a data training and analysis framework (DTAF). MDIR simplifies and reduces the cost of hosting digitalized content and metadata stored on Grid infrastructures, exploiting its features such as strong security contexts, data federation, and large storage and computing capacities.

MIWAD allows interaction with repository content and also offers low and high level image processing implementing full lifecycle CAD tasks: enhancing, segmentation, feature extraction, training, and the semiautomatic classification of digital mammograms. DTAF allows using Grid computing power to explore the search space of possible configurations of Artificial Neural Networks (ANN) based classifiers to find the ones that best classify mammography data. This was validated successfully (0.85 average area under the ROC curve) in a dataset of 100 selected mammograms with representative pathological lesions and normal cases from the MIAS database and the 699 cases of the UCI Breast Cancer Wisconsin dataset. Now, a pilot experience is taking place at the Faculty of Medicine in the Porto University, where MDIR and MIWAD technologies are being evaluated in a real medical environment.