ArticleIEEE access : practical innovations, open solutions2022
Lossless Compressed Sensing of Photon Counts for Fast Diffuse Correlation Spectroscopy.
Article in IEEE access : practical innovations, open solutions, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed, 0 citations in OpenAlex.
- Compact FPGA-based software correlator for real-time blood flow measurement with diffuse correlation spectroscopy.Biomedical optics express · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Diffuse Correlation Spectroscopy (DCS), a noninvasive optical technique, measures deep tissue blood flow using avalanche photon counting modules and data acquisition devices such as FPGAs or correlator boards. Conventional DCS instruments use in-processor counter modules that consume 32 bits/channel which is inefficient for low-photon budget situations prevalent in diffuse optics. Scaling these photon counters for large-scale imaging applications is difficult due to bandwidth and processing time considerations. Here, we introduce a new, lossless compressed sensing approach for fast and efficient detection of photon counts. The compressed DCS method uses an array of binary-coded-decimal counters to record photon counts from 8 channels simultaneously as a single 32-bit number. We validate the compressed DCS approach by comparisons with conventional DCS in experiments on tissue simulating phantoms and in-vivo arm cuff occlusion. Lossless compressed DCS was implemented with 87.5% compression efficiency. In tissue simulating phantoms, it was able to accurately estimate a tissue blood flow index, with no statistically significant difference compared to conventional DCS. Compressed DCS also recorded blood flow in vivo, in human forearm, with signal-to-noise ratio and dynamic range comparable to conventional DCS. Lossless 87.5% efficient compressed sensing counting of photon counts meets and exceeds benchmarks set by conventional DCS systems, offering a low-cost alternative for fast (~100 Hz) deep tissue blood flow measurement with optics.
Indexed as
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.