ArticleLight, science & applications2022
High-throughput volumetric adaptive optical imaging using compressed time-reversal matrix.
Article in Light, science & applications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 29 citations in OpenAlex.
- Dual deconvolution in multiphoton structured illumination microscopy for deep-tissue super-resolution imaging.Nature communications · 2026Article
- Matrix-based imaging through dynamic scattering.Nature communications · 2025Article
- Long-term tracking of neural and oligodendroglial development in large-scale human cerebral organoids by noninvasive volumetric imaging.Scientific reports · 2025Article
- Noninvasive megapixel fluorescence microscopy through scattering layers by a virtual incoherent reflection matrix.Science advances · 2024Article
- Twists through turbidity: propagation of light carrying orbital angular momentum through a complex scattering medium.Scientific reports · 2024Article
- Wavefront shaping improves the transparency of the scattering media: a review.Journal of biomedical optics · 2024Review
- In-silico clearing approach for deep refractive index tomography by partial reconstruction and wave-backpropagation.Light, science & applications · 2023Article
- Adaptive optics for optical microscopy [Invited].Biomedical optics express · 2023Review
- Wavefront shaping: A versatile tool to conquer multiple scattering in multidisciplinary fields.Innovation (Cambridge (Mass.)) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Deep-tissue optical imaging suffers from the reduction of resolving power due to tissue-induced optical aberrations and multiple scattering noise. Reflection matrix approaches recording the maps of backscattered waves for all the possible orthogonal input channels have provided formidable solutions for removing severe aberrations and recovering the ideal diffraction-limited spatial resolution without relying on fluorescence labeling and guide stars. However, measuring the full input-output response of the tissue specimen is time-consuming, making the real-time image acquisition difficult. Here, we present the use of a time-reversal matrix, instead of the reflection matrix, for fast high-resolution volumetric imaging of a mouse brain. The time-reversal matrix reduces two-way problem to one-way problem, which effectively relieves the requirement for the coverage of input channels. Using a newly developed aberration correction algorithm designed for the time-reversal matrix, we demonstrated the correction of complex aberrations using as small as 2% of the complete basis while maintaining the image reconstruction fidelity comparable to the fully sampled reflection matrix. Due to nearly 100-fold reduction in the matrix recording time, we could achieve real-time aberration-correction imaging for a field of view of 40 × 40 µm
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.