Heart Rate Estimation Based on Optical Flow: Enabling Smooth Angle Changes in Ultrasound Simulation


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.

Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSIGNALS
Henning Schäfer
Henning Schäfer

Zu meinen Forschungsinteressen zählen Deep Learning, Natural Language Processing, und Informationsextraktion.

Christoph M. Friedrich
Christoph M. Friedrich
Principal Investigator

My research interests include Machine Learning, Natural Language Processing, and Computer Vision.