ArticleScientific reports2019
Fluorescence imaging reversion using spatially variant deconvolution.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Real-time fidelity assessment of fluorescence molecular imaging without reference images.Journal of biomedical optics · 2026Article
- Reconstruction of fluorophore absorption and fluorescence lifetime using early photon mesoscopic fluorescence molecular tomography: a phantom study.Journal of biomedical optics · 2022Article
- Clinical translation and implementation of optical imaging agents for precision image-guided cancer surgery.European journal of nuclear medicine and molecular imaging · 2021Article
- Deconvolution for multimode fiber imaging: modeling of spatially variant PSF.Biomedical optics express · 2020Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fluorescence imaging opens new possibilities for intraoperative guidance and early cancer detection, in particular when using agents that target specific disease features. Nevertheless, photon scattering in tissue degrades image quality and leads to ambiguity in fluorescence image interpretation and challenges clinical translation. We introduce the concept of capturing the spatially-dependent impulse response of an image and investigate Spatially Adaptive Impulse Response Correction (SAIRC), a method that is proposed for improving the accuracy and sensitivity achieved. Unlike classical methods that presume a homogeneous spatial distribution of optical properties in tissue, SAIRC explicitly measures the optical heterogeneity in tissues. This information allows, for the first time, the application of spatially-dependent deconvolution to correct the fluorescence images captured in relation to their modification by photon scatter. Using experimental measurements from phantoms and animals, we investigate the improvement in resolution and quantification over non-corrected images. We discuss how the proposed method is essential for maximizing the performance of fluorescence molecular imaging in the clinic.
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Registered trials
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