arXiv subjects

Ninghe Liu

Publications and source records attributed to Ninghe Liu.

4 recordsLinked to original sources

arXiv2025

Optimized cerebral blood flow measurement in speckle contrast optical spectroscopy via refinement of noise calibration

Speckle contrast optical spectroscopy (SCOS) offers a non-invasive and cost-effective method for monitoring cerebral blood flow (CBF). However, extracting accurate CBF from SCOS necessitates precise noise pre-calibration. Errors from this can degrade CBF measurement fidelity, particularly when the overall signal level is low. Such errors primarily stem from residual speckle contrast associated with camera and shot noise, whose fluctuations exhibit a temporal structure that mimics cerebral blood volume (CBV) waveforms. We propose an optimization-based framework that performs an adaptive refinement of noise calibration, mitigating the CBV-mimicking artifacts by reducing the CBF-CBV waveform correlation. Validated on 10 human subjects, our approach effectively lowered the signal threshold for reliable CBF signal from 97 to 26 electrons per pixel for a 1920x1200 pixels SCOS system. This improvement enables more accurate and robust CBF measurements in SCOS, especially at large source-detector (SD) distances for deeper tissue interrogation.

eess.SP↗

arXiv2025

Quantitative Decomposition of Speckle Decorrelation for Inverse Problems in Complex Wave Scattering

Optical scattering remains one of the richest phenomena to study in classical optics. Wavefronts that are severely distorted due to scattering still carry significant information about the optical path upstream. Decoding typically starts with the autocorrelation function; yet the precise relationship between it and scatterer statistics still remains unexplored, hindering the model-based method for inverse problems. Here, we reveal that decorrelation due to backward scattering may be quantified as two distinct terms: the first expresses scattering from the surface, whereas the second is due to the volume beneath. The two terms encode higher-order statistics of their respective regimes within the specimen; Experimental studies on representative custom-made scatterers match theoretical predictions with an overall L1-error of less than 0.2%, providing an advanced forward model for various model-based inverse approaches. As a proof-of-concept, we present two examples, scatterer particle size estimation and reconstruction of the incident beam profile, to validate this improvement.

physics.optics↗

arXiv2024

Ptychographic non-line-of-sight imaging for depth-resolved visualization of hidden objects

Non-line-of-sight (NLOS) imaging enables the visualization of objects hidden from direct view, with applications in surveillance, remote sensing, and light detection and ranging. Here, we introduce a NLOS imaging technique termed ptychographic NLOS (pNLOS), which leverages coded ptychography for depth-resolved imaging of obscured objects. Our approach involves scanning a laser spot on a wall to illuminate the hidden objects in an obscured region. The reflected wavefields from these objects then travel back to the wall, get modulated by the wall's complex-valued profile, and the resulting diffraction patterns are captured by a camera. By modulating the object wavefields, the wall surface serves the role of the coded layer as in coded ptychography. As we scan the laser spot to different positions, the reflected object wavefields on the wall translate accordingly, with the shifts varying for objects at different depths. This translational diversity enables the acquisition of a set of modulated diffraction patterns referred to as a ptychogram. By processing the ptychogram, we recover both the objects at different depths and the modulation profile of the wall surface. Experimental results demonstrate high-resolution, high-fidelity imaging of hidden objects, showcasing the potential of pNLOS for depth-aware vision beyond the direct line of sight.

eess.IV↗

arXiv2023

Sparsity-regularized coded ptychography for robust and efficient lensless microscopy on a chip

Coded ptychography has emerged as a powerful technique for high-throughput, high-resolution lensless imaging. However, the trade-off between acquisition speed and image quality remains a significant challenge. To address this, we introduce a novel sparsity-regularized approach to coded ptychography that dramatically reduces the number of required measurements while maintaining high reconstruction quality. The reported approach, termed the ptychographic proximal total-variation (PPTV) solver, formulates the reconstruction task as a total variation regularized optimization problem. Unlike previous implementations that rely on specialized hardware or illumination schemes, PPTV integrates seamlessly into existing coded ptychography setups. Through comprehensive numerical simulations, we demonstrate that PPTV-driven coded ptychography can produce accurate reconstructions with as few as eight intensity measurements, a significant reduction compared to conventional methods. Convergence analysis confirms the robustness and stability of the PPTV algorithm. Experimental results from our optical prototype, featuring a disorder-engineered surface for wavefront modulation, validate PPTV's ability to achieve high-throughput, high-resolution imaging with a substantially reduced measurement burden. By enabling high-quality reconstructions from fewer measurements, PPTV paves the way for more compact, efficient, and cost-effective lensless microscopy systems on a chip, with potential applications in digital pathology, endoscopy, point-of-care diagnostics, and high-content screening.

eess.IV↗