Bengtsenreeves2697

We show an imaging comparison between coherent and magnitude averaging of a human finger knuckle joint in vivo with 121 dB sensitivity for the coherent case. Further, the benefits of computational downscaling in low sensitivity MHz-OCT systems are analyzed.Optical coherence tomography (OCT) of the ex vivo rat and human brain tissue samples is performed. The set of samples comprises intact white and gray matter, as well as human brain gliomas of the World Health Organization (WHO) Grades I-IV and glioma model 101.8 from rats. Analysis of OCT signals is aimed at comparing the physically reasonable properties of tissues, and determining the attenuation coefficient, parameter related to effective refractive index, and their standard deviations. Data analysis is based on the linear discriminant analysis and estimation of their dispersion in a four-dimensional principal component space. The results demonstrate the distinct contrast between intact tissues and low-grade gliomas and moderate contrast between intact tissues and high-grade gliomas. Particularly, the mean values of attenuation coefficient are 7.56±0.91, 3.96±0.98, and 5.71±1.49 mm-1 for human white matter, glioma Grade I, and glioblastoma, respectively. The significant variability of optical properties of high Grades and essential differences between rat and human brain tissues are observed. The dispersion of properties enlarges with increase of the glioma WHO Grade, which can be attributed to the growing heterogeneity of pathological brain tissues. The results of this study reveal the advantages and drawbacks of OCT for the intraoperative diagnosis of brain gliomas and compare its abilities separately for different grades of malignancy. The perspective of OCT to differentiate low-grade gliomas is highlighted by the low performance of the existing intraoperational methods and instruments.We present a new approach to diffuse correlation spectroscopy which overcomes the limited light throughput of single-mode photon counting techniques. Our system employs heterodyne holographic detection to allow parallel measurement of the power spectrum of a fluctuating electric field across thousands of modes, at the shot noise limit, using a conventional sCMOS camera. This yields an order of magnitude reduction in detector cost compared to conventional techniques, whilst also providing robustness to the effects of ambient light and an improved signal-to-noise ratio during in vitro experiments. We demonstrate a GPU-accelerated holographic demodulation system capable of processing the incoming data (79.4 M pixels per second) in real-time, and a novel Fourier domain model of diffuse correlation spectroscopy which permits the direct recovery of flow parameters from the measured data. Our detection and modelling strategy are rigorously validated by modulating the Brownian component of an optical tissue phantom, demonstrating absolute measurements of the Brownian diffusion coefficient in excellent agreement with conventional methods. find more We further demonstrate the feasibility of our system through in vivo measurement of pulsatile flow rates measured in the human forearm.We propose the signal quality index (SQI) algorithm as a novel tool for quantitatively assessing the functional near infrared spectroscopy (fNIRS) signal quality in a numeric scale from 1 (very low quality) to 5 (very high quality). The algorithm comprises two preprocessing steps followed by three consecutive rating stages. The results on a dataset annotated by independent fNIRS experts showed SQI performed significantly better (p less then 0.05) than PHOEBE (placing headgear optodes efficiently before experimentation) and SCI (scalp coupling index), two existing algorithms, in both quantitatively rating and binary classifying the fNIRS signal quality. Employment of the proposed algorithm to estimate the signal quality before processing the fNIRS signals increases certainty in the interpretations.Intravascular photoacoustic (IVPA) imaging technology enables the visualization of pathological characteristics (such as inflammation activities, lipid deposition) of the artery wall. Blood flushing is a necessary step in improving the imaging quality in in vivo IVPA imaging. But the limited imaging speed of the systems stretches their flushing time, which is an important obstacle of their clinical translations. In this paper, we report an improvement in IVPA/IVUS imaging speed to 100 frames per second. The high-speed imaging is demonstrated in rabbit in vivo, visualizing the nanoparticles accumulated on abdominal aorta wall at the wavelength of 1064 nm, in real time display. Blood flushing in vivo improves the IVPA signal-noise-ratio by around 3.5 dB. This study offers a stable, efficient and easy-to-use tool for instantaneous disease visualization and disease diagnosis in research and forwards IVPA/IVUS imaging technology towards clinical translations.Optical coherence tomography angiography (OCTA) imaging is a valuable tool for the visualization of retinal vasculature at an unprecedented level of details. However, due to relatively long time-interval between repeated scans in the conventional OCTA scanning protocol, the OCTA flow signal suffers from low dynamic range and loss of velocity-intensity correlation. The ability to distinguish fast and slow flow in the retina may provide a powerful tool for the assessment of early-stage retinal diseases such as vein occlusion. Here, we report a method to detect relative flow velocity in human retina using a 67.5 kHz spectral-domain OCTA device. By adapting the selection of A-scan time-intervals within a single OCTA acquisition and combining the resulting OCTA images, we expand the detectable velocity range. After a quantitative validation of this method performing microchannel flow experiments with varying flow velocities, we demonstrate this approach on human eyes using CIRRUS HD-OCT 5000 with AngioPlex (ZEISS, Dublin, CA) through a prototype scanning pattern.We present a multi-speckle diffuse correlation spectroscopy (DCS) system for measuring cerebral blood flow in the healthy adult human brain. In contrast to the need for a high frame rate camera to measure the multi-speckle intensity auto-correlation, we employ a low frame rate camera to measure the auto-correlation using the recently introduced multi-step volterra integral method (MVIM). The results are validated by comparison against the blood flow measured using standard DCS system.Brillouin imaging (BI) has become a valuable tool for micromechanical material characterisation, thanks to extensive progress in instrumentation in the last few decades. This powerful technique is contactless and label-free, thus making it especially suitable for biomedical applications. Nonetheless, to fully harness the non-contact and non-destructive nature of BI, transformational changes in instrumentation are still needed to extend the technology's utility into the domain of in vivo and in situ operation, which we foresee to be particularly crucial for wide spread usage of BI, e.g. in medical diagnostics and pathology screening. This work addresses this challenge by presenting the first demonstration of a fibre-optic Brillouin probe, capable of mapping the micromechanical properties of a tissue-mimicking phantom. This is achieved through combination of miniaturised optical design, advanced hollow-core fibre fabrication and high-resolution 3D printing. Our prototype probe is compact, background-free and possesses the highest collection efficiency to date, thus providing the foundation of a fibre-based Brillouin device for remote, in situ measurements in challenging and otherwise difficult-to-reach environments in biomedical, material science and industrial applications.The subtyping of Acute lymphocytic leukemia (ALL) is important for proper treatment strategies and prognosis. Conventional methods for manual blood and bone marrow testing are time-consuming and labor-intensive, while recent flow cytometric immunophenotyping has the limitations such as high cost. Here we develop the deep learning-based light scattering imaging flow cytometry for label-free classification of ALL. The single ALL cells confined in three dimensional (3D) hydrodynamically focused stream are excited by light sheet. Our label-free microfluidic cytometry obtains big-data two dimensional (2D) light scattering patterns from single ALL cells of B/T subtypes. A deep learning framework named Inception V3-SIFT (Scale invariant feature transform)-Scattering Net (ISSC-Net) is developed, which can perform high-precision classification of T-ALL and B-ALL cell line cells with an accuracy of 0.993 ± 0.003. Our deep learning-based 2D light scattering flow cytometry is promising for automatic and accurate subtyping of un-stained ALL.Excitation of dye-loaded perfluorocarbon nanoparticles (nanobombs) can generate highly localized axially propagating longitudinal shear waves (LSW) that can be used to quantify tissue mechanical properties without transversal scanning of the imaging beam. In this study, we used repetitive excitations of dodecafluoropentane (C5) and tetradecafluorohexane (C6) nanobombs by a nanosecond-pulsed laser to produce multiple LSWs from a single spot in a phantom. A 1.5 MHz Fourier-domain mode-locked laser in combination with a phase correction algorithm was used to perform elastography. Multiple nanobomb activations were also monitored by detecting photoacoustic signals. Our results demonstrate that C6 nanobombs can be used for repetitive generation of LSW from a single spot for the purpose of material elasticity assessment. This study opens new avenues for continuous quantification of tissue mechanical properties using single delivery of the nanoparticles.We report a cross-talk free simultaneous three-wavelength digital holographic microscopy setup for spectroscopic imaging of biological cells during flow. The feasibility of the proposed measurement technique is demonstrated on erythrocytes, due to their unique morphology and dependency of hemoglobin (Hb) molecule absorption on wavelength. From the spectroscopic quantitative phase profiles of cells acquired during flow in a microfluidic device, we decoupled the refractive index and the physical thickness. We then used our quantitative phase imaging results to dynamically calculate the mean cell volume (MCV), mean corpuscular Hb concentration (MCHC), mean corpuscular Hb content (MCH) and sphericity index.Two-photon microscopy (TPM) has been widely used in biological imaging owing to its intrinsic optical sectioning and deep penetration abilities. However, the conventional TPM suffers from poor axial resolution, which makes it difficult to recognize some three-dimensional fine features. We present multi-frame reconstruction two-photon microscopy (MR-TPM) using a liquid lens as a fast axial scanning engine. A sensorless adaptive optics (AO) approach is adopted to correct the aberrations caused by both the liquid lens and the optical system. By overcoming the effect of optical aberrations, inadequate sampling, and poor focusing capability of a conventional TPM, the axial resolution can be improved by a factor of 3 with a high signal-to-noise ratio. The proposed technology is compatible with the conventional TPM and requires no optical post-processing. We demonstrate the proposed method by imaging fluorescent beads, in vitro imaging of the neural circuit of mouse brain slice, and in vivo time-lapse imaging of the morphological changes of microglial cells in septic mice model.