ArticleScientific reports2022
Real-time, multi-spectral motion artefact correction and compensation for laser speckle contrast imaging.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- DASHING-LSCI: deep learning-based anatomical multiclass segmentation for human intraoperative neurosurgical guidance - laser speckle contrast imaging.Biomedical optics express · 2026Article
- On-skin, micro-objective enabled camera module for speckle contrast optical spectroscopy/tomography.Biomedical optics express · 2025Article
- Handheld laser speckle contrast imaging probe: quantitative video rate assessment of tissue perfusion in animal and patient applications.Biophotonics discovery · 2025Article
- Lightweight denoising speckle contrast image GAN for real-time denoising of laser speckle imaging of blood flow.Biomedical optics express · 2025Article
- Real-time quantification of laser speckle contrast imaging during intestinal laparoscopic surgery: successful demonstration in a porcine intestinal ischemia model.Surgical endoscopy · 2024Article
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Laser speckle contrast imaging (LSCI) is so sensitive to motion that it can measure the movement of red blood cells. However, this extreme sensitivity to motion is also its pitfall as the clinical translation of LSCI is slowed down due to the inability to deal with motion artefacts. In this paper we study the effectiveness of a real-time, multi-spectral motion artefact correction and compensation by subduing an in vitro flow phantom and ex vivo porcine kidney to computer-controlled motion artefacts. On the in vitro flow phantom, the optical flow showed a good correlation with the total movement. This model results in a better signal-to-noise ratios for multiple imaging distances and the overestimation of perfusion was reduced. In the ex vivo kidney model, the perfusion overestimation was also reduced and we were still able to distinguish between ischemia and non-ischemia in the stabilized data whereas this was not possible in the non-stabilized data. This leads to a notably better perfusion estimation that could open the door to a multitude of new clinical applications for LSCI.
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