Statistical Modeling and Segmentation in Cardiac MRI Using a Grid Computing Approach

Abstract. Grid technology is widely emerging as a solution for wide-spread applicability of computerized analysis and processing procedures in biomedical sciences. In this paper we show how a cardiac image analysis task can substantially benefit from Grids, making use of a middleware service tailored to the needs of common application tasks. In a first part we describe a methodology for the construction of three-dimensional (3D) statistical shape models of the heart, from a large image database of dynamic MRI studies. Non-rigid registration is needed for the automatic establishing of landmark correspondences across populations of healthy and diseased hearts; but when dealing with large databases, the computational load of current algorithms becomes a serious burden. Our Grid service API provided an easy way of taking benefit from our computing resources, by allowing for pipelining the distributed and non-distributed steps of the algorithm. As a second part of this work we show how t...

• Type: Conference
• Year: 2005
• Where: EGC
• Authors: Sebastián Ordas, Hans C. van Assen, Loic Boisrobert, Marcos Laucelli, Jesús Puente, Boudewijn P. F. Lelieveldt, Alejandro F. Frangi
• Keywords: Distributed And Parallel Computing, EGC 2005, Grid Service, MRI Studies, Shape Models