Single-photon vibrometry

Rehain, Patrick; Ramanathan, Jeevanandha; Sua, Yong Meng; Zhu, Shenyu; Tafone, Daniel; Huang, Yu‐Ping

doi:10.1364/ol.433423

Cited by 12 publications

(5 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This result is consistent with Ref. 10 . In both cases, the PNR plots clearly resemble the concentration but not the surface reflectivity, which confirms the results in Fig.…”

Section: Resultssupporting

confidence: 94%

“…Similar to OCE, SPV does not use a complex mathematical model to calculate Young’s modulus. 10 Instead, it directly measures the target’s mechanical response to applied external forces to obtain its elasticity and other physical properties. The second is QPMS, which maximally rejects the background noises from ambient light or multiscattering 11 so that the ultra-weak, single-photon level signals can be detected reliably despite much stronger noises.…”

Section: Introductionmentioning

confidence: 99%

“…The first is single-photon vibrometry (SPV), where the dynamic speckle pattern created by an oscillating surface is measured by a single-pixel and single-photon-counting light detection and ranging. Similar to OCE, SPV does not use a complex mathematical model to calculate Young’s modulus 10 . Instead, it directly measures the target’s mechanical response to applied external forces to obtain its elasticity and other physical properties.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Non-contact elasticity contrast imaging using photon counting

Zheng,

Meng Sua,

Zhu

et al. 2024

J. Biomed. Opt.

Self Cite

View full text Add to dashboard Cite

Significance: Tissues' biomechanical properties, such as elasticity, are related to tissue health. Optical coherence elastography produces images of tissues based on their elasticity, but its performance is constrained by the laser power used, working distance, and excitation methods.Aim: We develop a new method to reconstruct the elasticity contrast image over a long working distance, with only low-intensity illumination, and by non-contact acoustic wave excitation.Approach: We combine single-photon vibrometry and quantum parametric mode sorting (QPMS) to measure the oscillating backscattered signals at a single-photon level and derive the phantoms' relative elasticity.Results: We test our system on tissue-mimicking phantoms consisting of contrast sections with different concentrations and thus stiffness. Our results show that as the driving acoustic frequency is swept, the phantoms' vibrational responses are mapped onto the photon-counting histograms from which their mechanical propertiesincluding elasticity-can be derived. Through lateral and longitudinal laser scanning at a fixed frequency, a contrast image based on samples' elasticity can be reliably reconstructed upon photon level signals. Conclusions:We demonstrated the reliability of QPMS-based elasticity contrast imaging of agar phantoms in a long working distance, low-intensity environment. This technique has the potential for in-depth images of real biological tissue and provides a new approach to elastography research and applications.

show abstract

“…This result is consistent with Ref. 10 . In both cases, the PNR plots clearly resemble the concentration but not the surface reflectivity, which confirms the results in Fig.…”

Section: Resultssupporting

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Non-contact elasticity contrast imaging using photon counting

Zheng,

Meng Sua,

Zhu

et al. 2024

J. Biomed. Opt.

Self Cite

View full text Add to dashboard Cite

show abstract

“…This result is consistent with Ref. [24]. In both cases, the PNR plots clearly resemble the concentration but not the surface reflectivity, which confirms the results in Fig.…”

Section: Resultssupporting

confidence: 93%

Photon Counting Elastography

Huang,

Zheng,

Sua

et al. 2023

Preprint

View full text Add to dashboard Cite

We demonstrate a non-contact elastography with low-intensity illumination, mode-selective single photon detection, and acoustic excitation. It probes target samples with milliwatt, picosecond laser pulses and measures the backscattered photons via quantum parametric mode sorting and upconversion detection. As the acoustic frequency is swept, the samples' vibrational responses are mapped onto the photon counting histograms from which their mechanical properties--including elasticity--can be derived. By lateral and longitudinal laser scanning at a fixed frequency, an elastogram can be reliably reconstructed upon photon level signals. This technique has the potential for remote sensing and imaging of tissues and materials with differential mechanical properties in photon starved or restricted environment.

show abstract

“…The first is the noise rejection. In our expriment, QPMS rejects over 99.9% of noise 44 , so that the actual detected noise by the Si-SPD is only on the dark count level, much weaker than the signal, leading to the high accuracy. The second reason is with the much lower noise equivalence of dark counts (NEDC), defined as the detector dark count divided by the total detection efficiency.…”

Section: Resultsmentioning

confidence: 87%

Noise-Resilient Single-Pixel Compressive Sensing with Single Photon Counting

Huang,

Li,

Kumar

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

The fast expansion of photon detection technology has fertilized the rapid growth of single-photon sensing and imaging techniques. While promising significant advantages over their classical counterparts, they suffer from ambient and quantum noises whose effects become more pronounced at low light levels and thus must be addressed to achieve high quality results. Here we study how photon-counting noises degrade a single-pixel optical classifier via compressive sensing, and how its performance can be restored by using quantum parametric mode sorting (QPMS). Using MNIST handwritten digits as an example, we examine the effects of detector dark counts and in-band background noises, and demonstrate the effectiveness of mode filtering and upconversion detection in addressing those issues. We achieve 94% classification accuracy in the presence of 500 times stronger in-band noise than the signal received. Our results suggest a robust and efficient approach to single photon sensing in noisy environment.

show abstract

Single-photon vibrometry

Cited by 12 publications

References 24 publications

Non-contact elasticity contrast imaging using photon counting

Non-contact elasticity contrast imaging using photon counting

Photon Counting Elastography

Noise-Resilient Single-Pixel Compressive Sensing with Single Photon Counting

Contact Info

Product

Resources

About