Automated endoscopic capsule analysis using a Grid computing environment

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2010

Autores

Oliveira, IC (Autor) Outra; Alves, L (Autor) Outra; Dias, E (Autor) Outra; Pacheco, D (Autor) Outra; Lima, S (Autor) Outra; Barros, J (Autor) Outra; Miguel Pimenta Monteiro (Autor) FEUP; Jorge Alves Silva (Autor) FEUP; Fernandes, JM (Autor) Outra; Cunha, JPS (Autor) Outra; Pereira, AS (Autor) Outra

Ata de Conferência Internacional

Título: IBERGRID - 4th Iberian Grid Infrastructure Conference Proceedings

Páginas: 319-330

IBERGRID - Iberian Grid Infrastructure Conference

Indexação

ISI Web of Knowledge - 0 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

Outras Informações

ID Authenticus: P-008-W6H

Abstract (EN): With the increase of Endoscopic Capsule (EC) exams, the amount of video data to be analyzed by automated image processing algorithms grows exponentially and standard desktop computers start to present limitations to complete that procedure in an acceptable "clinical time". This has motivated us to assess the potential of Grid computing paradigm to process and analyze EC data, using existing Grid infrastructures. We used our Automated Topografic Segmentation (ATS) algorithm as a case study to run experiments on the Ibergrid Grid infrastructure. As a result, we were able to port the existing ATS algorithm used in routine to run on the Grid seamlessly. A friendly portal environment was adopted, allowing for clinical end-users to harness from existing production Grids in a practical way. The processing time could be reduced in some cases but, when considering job processing overheads, the desktop version is preferable for small scale processing. These results show that Grid computing is a promising technology to process massive amounts of EC data, but current infrastructures present a high variability in jobs processing times, especially when compared with dedicated clusters.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12