BibTex format
@article{Lerendegui:2024:10.1109/TMI.2024.3388048,
author = {Lerendegui, M and Riemer, K and Papageorgiou, G and Wang, B and Lachlan, A and Chavignon, A and Zhang, T and Couture, O and Huang, P and Ashikuzzaman, M and Dencks, S and Dunsby, C and Helfield, B and Jensen, ØA and Lisson, T and Lowerison, MR and Rivaz, H and Samir, AE and Schmitz, G and Schoen, S and Ruud, VS and Pengfei, S and Stevens, T and Yan, J and Sboros, V and Tang, M},
doi = {10.1109/TMI.2024.3388048},
journal = {IEEE Transactions on Medical Imaging},
title = {ULTRA-SR challenge: assessment of UltrasoundLocalization and TRacking Algorithms for Super-Resolution Imaging},
url = {http://dx.doi.org/10.1109/TMI.2024.3388048},
year = {2024}
}
RIS format (EndNote, RefMan)
TY - JOUR
AB - With the widespread interest and uptake of super-resolution ultrasound (SRUS) through localization and tracking of microbubbles, also known as ultrasound localization microscopy (ULM), many localization and tracking algorithms have been developed. ULM can image many centimeters into tissue in-vivo and track microvascular flow non-invasively with sub-diffraction resolution. In a significant community effort, we organized a challenge, Ultrasound Localization and TRacking Algorithms for Super-Resolution (ULTRA-SR). The aims of this paper are threefold: to describe the challenge organization, data generation, and winning algorithms; to present the metrics and methods for evaluating challenge entrants; and to report results and findings of the evaluation. Realistic ultrasound datasets containing microvascular flow for different clinical ultrasound frequencies were simulated, using vascular flow physics, acoustic field simulation and nonlinear bubble dynamics simulation. Based on these datasets, 38 submissions from 24 research groups were evaluated against ground truth using an evaluation framework with six metrics, three for localization and three for tracking. In-vivo mouse brain and human lymph node data were also provided, and performance assessed by an expert panel. Winning algorithms are described and discussed. The publicly available data with ground truth and the defined metrics for both localization and tracking present a valuable resource for researchers to benchmark algorithms and software, identify optimized methods/software for their data, and provide insight into the current limits of the field. In conclusion, Ultra-SR challenge has provided benchmarking data and tools as well as direct comparison and insights for a number of the state-of-the art localization and tracking algorithms.
AU - Lerendegui,M
AU - Riemer,K
AU - Papageorgiou,G
AU - Wang,B
AU - Lachlan,A
AU - Chavignon,A
AU - Zhang,T
AU - Couture,O
AU - Huang,P
AU - Ashikuzzaman,M
AU - Dencks,S
AU - Dunsby,C
AU - Helfield,B
AU - Jensen,ØA
AU - Lisson,T
AU - Lowerison,MR
AU - Rivaz,H
AU - Samir,AE
AU - Schmitz,G
AU - Schoen,S
AU - Ruud,VS
AU - Pengfei,S
AU - Stevens,T
AU - Yan,J
AU - Sboros,V
AU - Tang,M
DO - 10.1109/TMI.2024.3388048
PY - 2024///
SN - 0278-0062
TI - ULTRA-SR challenge: assessment of UltrasoundLocalization and TRacking Algorithms for Super-Resolution Imaging
T2 - IEEE Transactions on Medical Imaging
UR - http://dx.doi.org/10.1109/TMI.2024.3388048
UR - https://ieeexplore.ieee.org/document/10497610
UR - http://hdl.handle.net/10044/1/111652
ER -
