Publications by authors named "Brett Bouma"

Photoacoustic microscopy (PAM) is a high-resolution and non-invasive imaging modality that provides optical absorption contrast. By employing dual- or multiple-wavelength excitation, PAM extends its capabilities to offer valuable spectroscopic information. To achieve efficient multispectral PAM imaging, an essential requirement is a light source characterized by a high repetition rate and switching rate, a ≈microjoule pulse energy, and a ≈nanosecond pulse duration.

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Imaging depth-resolved birefringence and optic axis orientation with polarization sensitive optical coherence tomography (PS-OCT) unveils details of tissue structure and organization that can be of high pathophysiologic, mechanistic, and diagnostic value. For catheter-based PS-OCT, the dynamic rotation of the fiber optic probe, in addition to the polarization effects of the system components, complicates the reliable and robust reconstruction of the sample's optic axis orientation. Addressing this issue, we present a new method for the reconstruction of absolute depth-resolved optic axis orientation in catheter-based PS-OCT by using the intrinsic retardance of the protecting catheter sheath as a stable guide star signal.

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We propose a new simple and cost-effective optical imaging technique, full-field amplitude speckle decorrelation angiography (FASDA), capable of visualizing skin microvasculature with high resolution, and sensitive to small, superficial vessels with slow blood flow and larger, deeper vessels with faster blood flow. FASDA makes use of a laser source with limited temporal coherence, can be implemented with cameras with conventional frame rates, and does not require raster scanning. The proposed imaging technique is based on the simultaneous evaluation of two metrics: the blood flow index, a contrast-based metric used in laser speckle contrast imaging, and the adaptive speckle decorrelation index (ASDI), a new metric that we defined based on the second-order autocorrelation function that considers the limited speckle modulation that occurs in partially-coherent imaging.

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We present a deep learning framework for volumetric speckle reduction in optical coherence tomography (OCT) based on a conditional generative adversarial network (cGAN) that leverages the volumetric nature of OCT data. In order to utilize the volumetric nature of OCT data, our network takes partial OCT volumes as input, resulting in artifact-free despeckled volumes that exhibit excellent speckle reduction and resolution preservation in all three dimensions. Furthermore, we address the ongoing challenge of generating ground truth data for supervised speckle suppression deep learning frameworks by using volumetric non-local means despeckling-TNode- to generate training data.

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Speckle degrades the quality of optical coherence tomography (OCT) images and impedes their visual interpretation. Current hardware methods for speckle suppression necessitate difficult hardware modifications. As a result, algorithmic approaches for speckle suppression generally lack validation or training with physically meaningful ground truth.

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Deep venous thrombosis (DVT) is a medical condition with significant post-event morbidity and mortality coupled with limited treatment options. Treatment strategy and efficacy are highly dependent on the structural composition of the thrombus, which evolves over time from initial formation and is currently unevaluable with standard clinical testing. Here, we investigate the use of intravascular polarization-sensitive optical coherence tomography (PS-OCT) to assess thrombus morphology and composition in a rat DVT model , including changes that occur over the thrombus aging process.

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The clinical management of coronary artery disease and the prevention of acute coronary syndromes require knowledge of the underlying atherosclerotic plaque pathobiology. Hybrid imaging modalities capable of comprehensive assessment of biochemical and morphological plaques features can address this need. Here we report the first implementation of an intravascular catheter system combining fluorescence lifetime imaging (FLIm) with polarization-sensitive optical coherence tomography (PSOCT).

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Intravascular ultrasound and optical coherence tomography are widely available for assessing coronary stenoses and provide critical information to optimize percutaneous coronary intervention. Intravascular polarization-sensitive optical coherence tomography (PS-OCT) measures the polarization state of the light scattered by the vessel wall in addition to conventional cross-sectional images of subsurface microstructure. This affords reconstruction of tissue polarization properties and reveals improved contrast between the layers of the vessel wall along with insight into collagen and smooth muscle content.

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We present a deep learning framework for volumetric speckle reduction in optical coherence tomography (OCT) based on a conditional generative adversarial network (cGAN) that leverages the volumetric nature of OCT data. In order to utilize the volumetric nature of OCT data, our network takes partial OCT volumes as input, resulting in artifact-free despeckled volumes that exhibit excellent speckle reduction and resolution preservation in all three dimensions. Furthermore, we address the ongoing challenge of generating ground truth data for supervised speckle suppression deep learning frameworks by using volumetric non-local means despeckling-TNode to generate training data.

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The guest editors introduce a feature issue commemorating the 30th anniversary of Optical Coherence Tomography.

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Optical coherence tomography (OCT) leverages light scattering by biological tissues as endogenous contrast to form structural images. Light scattering behavior is dictated by the optical properties of the tissue, which depend on microstructural details at the cellular or sub-cellular level. Methods to measure these properties from OCT intensity data have been explored in the context of a number of biomedical applications seeking to access this sub-resolution tissue microstructure and thereby increase the diagnostic impact of OCT.

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Intravascular polarimetry with catheter-based polarization-sensitive optical coherence tomography (PS-OCT) complements the high-resolution structural tomograms of OCT with morphological contrast available through polarimetry. Its clinical translation has been complicated by the need for modification of conventional OCT hardware to enable polarimetric measurements. Here, we present a signal processing method to reconstruct the polarization properties of tissue from measurements with a single input polarization state, bypassing the need for modulation or multiplexing of input states.

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We present computational refocusing in polarization-sensitive optical coherence tomography (PS-OCT) to improve spatial resolution in the calculated polarimetric parameters and extend the depth-of-field in phase-unstable, fiber-based PS-OCT systems. To achieve this, we successfully adapted short A-line range phase-stability adaptive optics (SHARP), a computational aberration correction technique compatible with phase-unstable systems, into a Stokes-based PS-OCT system with inter-A-line polarization modulation. Together with the spectral binning technique to mitigate system-induced chromatic polarization effects, we show that computational refocusing improves image quality in tissue polarimetry of swine eye anterior segment ex vivo with PS-OCT.

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Dispersion remains an enduring challenge for the characterization of wavelength-dependent transmission through optical multimode fiber (MMF). Beyond a small spectral correlation width, a change in wavelength elicits a seemingly independent distribution of the transmitted field. Here we report on a parametric dispersion model that describes mode mixing in MMF as an exponential map and extends the concept of principal modes to describe the fiber's spectrally resolved transmission matrix (TM).

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Polarization sensitive optical coherence tomography (PSOCT) has been shown to image and delineate white matter fibers in a label-free manner by revealing optical birefringence within the myelin sheath using a microscope setup. In this proof-of-concept study, we adapt recent advancements in endoscopic PSOCT to perform depth-resolved imaging of white matter structures deep inside intact porcine brain tissue ex-vivo, through a small, rotational fiber probe. The probe geometry is comparable to microelectrodes currently used in neurosurgical interventions.

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Article Synopsis
  • Microscopic imaging in 3D faces challenges due to diffraction that limits high-resolution optical imaging over a large depth range.
  • A new approach using specific light paths with metasurfaces creates a direct relationship between incident and collected light, allowing for improved imaging.
  • This technique, called bijective illumination collection imaging, achieves high-resolution tissue imaging at 1.3 μm wavelength with approximately 3.2 μm lateral resolution, maintaining clarity over a 1.25 mm depth without extra complexity in data processing.
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Determining the optimal treatment course for a dermatologic burn wound requires knowledge of the wound's severity, as quantified by the depth of thermal damage. In current clinical practice, burn depth is inferred based exclusively on superficial visual assessment, a method which is subject to substantial error rates in the classification of partial thickness (second degree) burns. Here, we present methods for direct, quantitative determination of the depth extent of injury to the dermal collagen matrix using polarization-sensitive optical coherence tomography (PS-OCT).

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Article Synopsis
  • Optical Coherence Tomography (OCT) has evolved as a key imaging tool over the past two decades, significantly improving our understanding of coronary atherosclerosis and optimizing cardiac interventions.
  • Recent advancements in OCT have enabled better identification of plaque pathology and healing processes in patients with acute coronary syndromes, potentially transforming patient management.
  • This Review aims to present the latest insights on cardiac OCT, standardizing its clinical application and interpretation among researchers and clinicians globally.
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Imaging through optical multimode fiber (MMF) has the potential to enable hair-thin endoscopes that reduce the invasiveness of imaging deep inside tissues and organs. Active wavefront shaping and fluorescent labeling have recently been exploited to overcome modal scrambling and enable MMF imaging. Here, we present a computational approach that circumvents the need for active wavefront control and exogenous fluorophores.

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Near-infrared photoacoustics receives increasing interest as an intravital modality to sense key biomolecules. One of the most central types of biomolecules of interest are lipids as they constitute essential bio-hallmarks of cardiovascular and metabolic diseases and their in-vivo detection holds insightful information about disease progression and treatment monitoring. However, the full potential of near-infrared photoacoustic for high-resolution and high-sensitivity biomedical studies of lipids has so far not been exploited due a lack of appropriate excitation sources delivering short-pulses at high-repetition-rate, high-pulse-energy, and wavelength around 1200 nm.

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Polarization-sensitive optical coherence tomography (PS-OCT) reveals the subsurface microstructure of biological tissue and provides information regarding the polarization state of light backscattered from tissue. Complementing OCT's structural signal with molecular imaging requires strategies to simultaneously detect multiple exogenous contrast agents with high specificity in tissue. Specific detection of molecular probes enables the parallel visualization of physiological, cellular, and molecular processes.

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Structural optical coherence tomography (OCT) images of tissue stand to benefit from greater functionalization and quantitative interpretation. The OCT attenuation coefficient , an analogue of the imaged sample's scattering coefficient, offers potential functional contrast based on the relationship of to sub-resolution physical properties of the sample. Attenuation coefficients are computed either by fitting a representative over several depth-wise pixels of a sample's intensity decay, or by using previously-developed depth-resolved attenuation algorithms by Girard [Invest.

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Imaging whole brains is one of the central efforts of biophotonics. While the established imaging modalities used in radiology, such as MRI and CT, have enabled in vivo investigations of various cognitive and affective processes, the prevailing resolution of one-cubic-millimeter has limited their use in studying the "ground-truth" of neuronal activities. On the other hand, electron microscopy (EM) visualizes the finest anatomic structures at a resolution of around 30 nm.

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