TY - CHAP AU - Hanne Kause AU - Aura Hernandez-Sabate AU - Patricia Marquez AU - Andrea Fuster AU - Luc Florack AU - Hans van Assen AU - Debora Gil A2 - STACOM PY - 2015// TI - Confidence Measures for Assessing the HARP Algorithm in Tagged Magnetic Resonance Imaging T2 - LNCS BT - Statistical Atlases and Computational Models of the Heart. Revised selected papers of Imaging and Modelling Challenges 6th International Workshop, STACOM 2015, Held in Conjunction with MICCAI 2015 SP - 69 EP - 79 VL - 9534 PB - Springer International Publishing N2 - Cardiac deformation and changes therein have been linked to pathologies. Both can be extracted in detail from tagged Magnetic Resonance Imaging (tMRI) using harmonic phase (HARP) images. Although point tracking algorithms have shown to have high accuracies on HARP images, these vary with position. Detecting and discarding areas with unreliable results is crucial for use in clinical support systems. This paper assesses the capability of two confidence measures (CMs), based on energy and image structure, for detecting locations with reduced accuracy in motion tracking results. These CMs were tested on a database of simulated tMRI images containing the most common artifacts that may affect tracking accuracy. CM performance is assessed based on its capability for HARP tracking error bounding and compared in terms of significant differences detected using a multi comparison analysis of variance that takes into account the most influential factors on HARP tracking performance. Results showed that the CM based on image structure was better suited to detect unreliable optical flow vectors. In addition, it was shown that CMs can be used to detect optical flow vectors with large errors in order to improve the optical flow obtained with the HARP tracking algorithm. SN - 0302-9743 SN - 978-3-319-28711-9 L1 - http://refbase.cvc.uab.es/files/KHM2015.pdf UR - http://dx.doi.org/10.1007/978-3-319-28712-6_8 N1 - ADAS; IAM; 600.075; 600.076; 600.060; 601.145 ID - Hanne Kause2015 ER -