Authors:
Henning Schäfer
1
;
2
;
Hendrik Damm
1
;
3
and
Christoph M. Friedrich
1
;
4
Affiliations:
1
Department of Computer Science, University of Applied Sciences and Arts Dortmund (FHDO), Dortmund, NRW, Germany
;
2
Institute for Transfusion Medicine, University Hospital Essen, Essen, NRW, Germany
;
3
Institute of Epidemiology and Social Medicine, University of Münster, Münster, NRW, Germany
;
4
Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital Essen, Essen, NRW, Germany
Keyword(s):
Biomedical Image Processing, Ultrasound Imaging, Vascular Imaging, Image Visualization, Functional Image Analysis, 3D Video-based Ultrasound Simulation.
Abstract:
Ultrasound simulators show previously recorded ultrasound videos from different angles to the trainee. During
acquisition, breathing, pulse, and other motion artifacts are involved, which often prevent a smooth image
transition between different angles during simulation. In this work, a global motion vector is derived using
the Lucas–Kanade method for calculating the optical flow in order to create a motion profile in addition to the
recording. This profile allows transition synchronization in ultrasound simulators. For the transition in kidney
recordings, the Pearson’s r correlation could be increased from 0.252 to 0.495 by autocorrelating motion
profiles and synchronizing them based on calculated delays. Approaches based on tracking and structural
similarity were also evaluated, yet these have shown inferior qualitative transition results. In ultrasound videos
with visibility of vessels, e.g., thyroid gland with carotid artery or echocardiogram, the heart rate can also be
estimated via the optical flow. In the abdominal region, the signal contains respiratory information. Since the
motion profile can be generated in real time directly at the transducer position, it could be useful for diagnostic
purposes.
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