Talks and Poster Presentations (with Proceedings-Entry):

J. Dorazil, R. Repp, T. Kropfreiter, R. Prüller, K. Riha, F. Hlawatsch:
"Feature drift resilient tracking of the carotid artery wall using unscented Kalman filtering with data fusion";
Talk: 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona Spain (virtual); 05-04-2020 - 05-08-2020; in: "Ieee Icassp 2020", IEEE, (2020), ISBN: 978-1-5090-6631-5; 1095 - 1099.

English abstract:
An analysis of the motion of the common carotid artery (CCA) provides effective indicators for cardiovascular diseases. Here, we propose a method for tracking CCA wall motion from a B-mode ultrasound video sequence. An unscented Kalman filter based on a suitably devised state-space model fuses measurements produced by an optical flow algorithm and a CCA wall localization algorithm. This approach compensates for feature drift, which is a detrimental effect in optical flow algorithms. The proposed method is demonstrated to outperform a state-of-the-art tracking method based on optical flow.

Atherosclerosis, common carotid artery, B-mode ultrasound, unscented Kalman filter, data fusion

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.