BibTex format
蔼补谤迟颈肠濒别调骋辞苍锄谩濒别锄:2026:10.1016/箩.耻濒迟谤补蝉尘别诲产颈辞.2026.03.024,
author = {Gonz谩lez, CR and Huang, B and Yan, S and Zaydullin, R and Lerendegui, M and Smith, CAB and Toulemonde, M and Morris, M and Somaiah, N and Bates, O and Ng, FS and Tang, M-X},
doi = {10.1016/j.ultrasmedbio.2026.03.024},
journal = {Ultrasound Med Biol},
pages = {1544--1558},
title = {Benchmarking Image-Based Motion-Correction Methods for Ultrasound Localization Microscopy.},
url = {http://dx.doi.org/10.1016/j.ultrasmedbio.2026.03.024},
volume = {52},
year = {2026}
}
RIS format (EndNote, RefMan)
TY - JOUR
AB - BACKGROUND: Ultrasound localization microscopy (ULM) achieves sub-diffraction resolution imaging in vivo through localizing and tracking microbubbles. However, the need to accumulate microbubble signals over time makes ULM highly sensitive to tissue motion, necessitating accurate motion correction. The accuracy of motion-correction techniques poses a limit to the attainable resolution, and there is currently no gold standard algorithm or approach. METHODS: This study benchmarked seven publicly available implementations of non-rigid image registration algorithms using two simulated datasets illustrating soft tissue and cardiac images, as well as in vivo acquisitions of a rabbit kidney and human breast tumor. Five benchmarks were used to evaluate the seven implementations using image-based similarity metrics, errors against ground truth deformation fields, robustness to hyperparameter choice and image quality, including data with varying contrast-to-noise ratios. Using Bayesian optimization and Sobol sensitivity analysis, optimal parameters for each algorithm were identified, with guidelines for data-adaptive algorithm selection proposed. RESULTS: Parameter sensitivity analysis was reported for all implementations, which can be used to prioritize parameters when performing optimization. Motion characteristics and image spatial heterogeneity were found to be important factors for implementation accuracy. Spline-based algorithms, such as free-form deformations implemented in Elastix, performed optimally with small deformations and low spatial heterogeneity. In contrast, methods designed for large deformations, such as large deformation metric matching, implemented by Ceritoglu et al., or free-form deformations with diffeomorphic constraints, such as Niftyreg, were effective at correcting larger data displacements with high heterogeneity, but struggled to identify accurate correspondences when deformation magnitudes were small. Invertibility was beneficial when correctin
AU - Gonz谩lez,CR
AU - Huang,B
AU - Yan,S
AU - Zaydullin,R
AU - Lerendegui,M
AU - Smith,CAB
AU - Toulemonde,M
AU - Morris,M
AU - Somaiah,N
AU - Bates,O
AU - Ng,FS
AU - Tang,M-X
DO - 10.1016/j.ultrasmedbio.2026.03.024
EP - 1558
PY - 2026///
SP - 1544
TI - Benchmarking Image-Based Motion-Correction Methods for Ultrasound Localization Microscopy.
T2 - Ultrasound Med Biol
UR - http://dx.doi.org/10.1016/j.ultrasmedbio.2026.03.024
UR - https://www.ncbi.nlm.nih.gov/pubmed/42168000
VL - 52
ER -