onr:"swepub:oai:lup.lub.lu.se:b6c67cca-1207-4134-8c7b-0ca0c679e4db"
Sökning: onr:"swepub:oai:lup.lub.lu.se:b6c67cca-1207-4134-8c7b-0ca0c679e4db" > Transient Motion Cl...
- 1 av 1
- Föregående post
- Nästa post
- Till träfflistan
Transient Motion Classification Through Turbid Volumes via Parallelized Single-Photon Detection and Deep Contrastive Embedding
-
- Xu, Shiqi (författare)
- Duke University
-
- Liu, Wenhui (författare)
- Tsinghua University,Duke University
-
- Yang, Xi (författare)
- Duke University
- visa fler...
- visa färre...
- (creator_code:org_t)
- 2022-07-08
- 2022
- Engelska.
- Ingår i: Frontiers in Neuroscience. - : Frontiers Media SA. - 1662-4548 .- 1662-453X. ; 16
- Tidskriftsartikel (refereegranskat)
Abstract
Ämnesord
Stäng
- Fast noninvasive probing of spatially varying decorrelating events, such as cerebral blood flow beneath the human skull, is an essential task in various scientific and clinical settings. One of the primary optical techniques used is diffuse correlation spectroscopy (DCS), whose classical implementation uses a single or few single-photon detectors, resulting in poor spatial localization accuracy and relatively low temporal resolution. Here, we propose a technique termed Classifying Rapid decorrelation Events via Parallelized single photon dEtection (CREPE), a new form of DCS that can probe and classify different decorrelating movements hidden underneath turbid volume with high sensitivity using parallelized speckle detection from a 32 × 32 pixel SPAD array. We evaluate our setup by classifying different spatiotemporal-decorrelating patterns hidden beneath a 5 mm tissue-like phantom made with rapidly decorrelating dynamic scattering media. Twelve multi-mode fibers are used to collect scattered light from different positions on the surface of the tissue phantom. To validate our setup, we generate perturbed decorrelation patterns by both a digital micromirror device (DMD) modulated at multi-kilo-hertz rates, as well as a vessel phantom containing flowing fluid. Along with a deep contrastive learning algorithm that outperforms classic unsupervised learning methods, we demonstrate our approach can accurately detect and classify different transient decorrelation events (happening in 0.1–0.4 s) underneath turbid scattering media, without any data labeling. This has the potential to be applied to non-invasively monitor deep tissue motion patterns, for example identifying normal or abnormal cerebral blood flow events, at multi-Hertz rates within a compact and static detection probe.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Annan medicinteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Other Medical Engineering (hsv//eng)
Nyckelord
- contrastive learning
- diffuse correlation
- multimode fiber
- neurobehavior
- self-supervised learning
- SPAD array
- zero-shot learning
Publikations- och innehållstyp
- art (ämneskategori)
- ref (ämneskategori)
Hitta via bibliotek
- Frontiers in Neuroscience (Sök värdpublikationen i LIBRIS)
Till lärosätets databas
- 1 av 1
- Föregående post
- Nästa post
- Till träfflistan
Hitta mer i SwePub
- Av författaren/redakt...
- Xu, Shiqi
- Liu, Wenhui
- Yang, Xi
- Jönsson, Joakim
- Qian, Ruobing
- McKee, Paul
- visa fler...
- Kim, Kanghyun
- Konda, Pavan Cha ...
- Zhou, Kevin C.
- Kreiß, Lucas
- Wang, Haoqian
- Berrocal, Edouar ...
- Huettel, Scott A ...
- Horstmeyer, Roar ...
- visa färre...
- Om ämnet
-
- TEKNIK OCH TEKNOLOGIER
- TEKNIK OCH TEKNO ...
- och Medicinteknik
- och Annan medicintek ...
- Artiklar i publikationen
- Frontiers in Neu ...
- Av lärosätet
- Lunds universitet
Sök utanför SwePub
- Sök vidare i:
- Google Book Search
- Google Scholar
Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.
- Copyright © LIBRIS - Nationella bibliotekssystem
- LIBRIS.kb.se
