Benchmarking framework for myocardial tracking and deformation algorithms: an open access databaseReport as inadecuate




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1 Division of Imaging Sciences 2 Medisys - MedisysResearch Lab 3 ASCLEPIOS - Analysis and Simulation of Biomedical Images CRISAM - Inria Sophia Antipolis - Méditerranée 4 Department of Medical Engineering and Neuroprosthetics 5 Department of Computing London 6 Ulm University 7 CISTIB - Center for Computational Imaging and Simulation Technologies in Biomedicine 8 SICS 9 Siemens Corporate Research 10 UCL-CS - Computer science department University College London

Abstract : In this paper we present a benchmarking framework for the validation of cardiac motion analysis algorithms. The reported methods are the response to an open challenge that was put to the medical imaging community through a MICCAI workshop. The database included magnetic resonance MR and 3D ultrasound 3DUS datasets from a dynamic phantom and 15 healthy volunteers. Participants processed 3D tagged MR datasets 3DTAG, cine steady state free precession MR datasets SSFP and 3DUS datasets, amounting to 1158 image volumes. Ground-truth for motion tracking was based on 12 landmarks 4 walls at 3 ventricular levels. They were manually tracked by two observers in the 3DTAG data over the whole cardiac cycle, using an in-house application with 4D visualization capabilities. The median of the inter-observer variability was computed for the phantom dataset 0.77mm and for the volunteer datasets 0.84mm. The ground-truth was registered to 3DUS coordinates using a point based similarity transform. Four institutions responded to the challenge by providing motion estimates for the data: Fraunhofer MEVIS MEVIS, Bremen, Germany; Imperial College London - University College London IUCL, UK; Universitat Pompeu Fabra UPF, Barcelona, Spain; Inria-Asclepios project INRIA, France. Details on the implementation and evaluation of the four methodologies are presented in this manuscript. The manually tracked landmarks were used to evaluate tracking accuracy of all methodologies. For 3DTAG, median values were computed over all time frames for the phantom dataset MEVIS=1.20mm, IUCL=0.73mm, UPF=1.10mm, INRIA=1.09mm and for the volunteer datasets MEVIS=1.33mm, IUCL=1.52mm, UPF=1.09mm, INRIA=1.32mm. For 3DUS, median values were computed at end diastole and end systole for the phantom dataset MEVIS=4.40mm, UPF=3.48mm, INRIA=4.78mm and for the volunteer datasets MEVIS=3.51mm, UPF=3.71mm, INRIA=4.07mm. For SSFP, median values were computed at end diastole and end systole for the phantom dataset UPF=6.18mm, INRIA=3.93mm and for the volunteer datasets UPF=3.09mm, INRIA=4.78mm. Finally, strain curves were generated and qualitatively compared. Good agreement was found between the di erent modalities and methodologies, except for radial strain that showed a high variability in cases of lower image quality.





Author: Catalina Tobon-Gomez - Mathieu De Craene - Kristin Mcleod - Lennart Tautz - Wenzhe Shi - Anja Hennemuth - Adityo Prakosa - Hengui

Source: https://hal.archives-ouvertes.fr/



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