A Multimodal Database for the 1^st Cardiac Motion Analysis Challenge

Abstract

This paper describes the acquisition of the multimodal database used in the 1 ^st Cardiac Motion Analysis Challenge. The database includes magnetic resonance (MR) and 3D ultrasound (3DUS) datasets from a dynamic phantom and 15 datasets from healthy volunteers. The MR acquisition included cine steady state free precession (SSFP), whole-heart turbo field echo (TFE), and 4D tagged MR (tMR) sequences. From the SSFP images, the end diastolic anatomy was extracted using a deformable model of the left ventricle (LV). The LV model was mapped to the tMR coordinates using DICOM information. From the LV model, 12 landmarks were generated (4 walls at 3 ventricular levels). These landmarks were manually tracked in the tMR data over the whole cardiac cycle by two observes using an in-house application with 4D visualization capabilities. Finally, the LV model was registered to the 3DUS coordinates using a point based similarity transform. Four institutions responded to the challenge by providing motion estimates for the data. Preliminary results are presented for one of the volunteer data sets.