Publications by authors named "Changhuei Yang"

Using our recently developed laser speckle contrast imaging (LSCI) to visualize blood vessels and monitor blood flow noninvasively, we test the utility of the developing chick heart as a functional model for drug screening. To this end, we examined the effects of antihypertensive agents Nifedipine and Amlodipine, belonging to the L-type calcium channel antagonist family, on blood flow visualized noninvasively through the intact shell. Guided by the live view mode, the drugs were injected through the shell and ventral to HH16-19 chick embryos.

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In regional cerebrovascular monitoring, cerebral blood flow (CBF) and cerebral blood volume (CBV) are key metrics. Simultaneous, non-invasive measurement of CBF and CBV at different brain locations would advance cerebrovascular monitoring and pave the way for brain injury detection, as current brain injury diagnostic methods are often constrained by high costs, limited sensitivity, and reliance on subjective symptom reporting. This study's aim is to develop a multi-channel non-invasive optical system for measuring CBF and CBV at different regions of the brain simultaneously with a cost-effective, reliable, and scalable system capable of detecting potential differences in CBF and CBV across different regions of the brain.

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Deep neural network (DNN) models, particularly convolutional neural networks (CNNs), have demonstrated remarkable performance in biomedical image classification due to their ability to automatically learn features from large datasets. One common challenge in the preparation of large, microscopic datasets for DNN tasks is sample defocusing, potentially impairing the model performance. To handle defocusing, computational imaging, or specifically quantitative phase imaging (QPI), performs digital refocusing by using both the phase and the amplitude of the complex optical field.

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Article Synopsis
  • Whole slide imaging enhances pathological analysis by providing detailed images of biopsy or surgical samples, improving clinical diagnosis and patient treatment planning.
  • The newly developed WSI-APIC system utilizes angular ptychographic imaging for high-quality, tens-of-gigapixels images while eliminating the need for z-scanning and reducing background scanning.
  • This system achieves an optical resolution of 772 nm and seamlessly stitches together phase images, allowing for efficient and aberration-free visualization on standard microscopic slides.
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Stroke poses a significant global health threat, with millions affected annually, leading to substantial morbidity and mortality. Current stroke risk assessment for the general population relies on markers such as demographics, blood tests, and comorbidities. A minimally invasive, clinically scalable, and cost-effective way to directly measure cerebral blood flow presents an opportunity.

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Imaging blood vessels in early-stage avian embryos has a wide range of practical applications for developmental biology studies, drug and vaccine testing, and early sex determination. Optical imaging, such as brightfield transmission imaging, offers a compelling solution due to its safe non-ionizing radiation, and operational benefits. However, it comes with challenges, such as eggshell opacity and light scattering.

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Deep learning-assisted digital pathology has demonstrated the potential to profoundly impact clinical practice, even surpassing human pathologists in performance. However, as deep neural network (DNN) architectures grow in size and complexity, their explainability decreases, posing challenges in interpreting pathology features for broader clinical insights into physiological diseases. To better assess the interpretability of digital microscopic images and guide future microscopic system design, we developed a novel method to study the predictive feature length-scale that underpins a DNN's predictive power.

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Article Synopsis
  • Recent advances in deep neural networks (DNNs) have shown they can sometimes outperform expert pathologists in analyzing pathology images by learning intricate details from large datasets.
  • The research highlighted issues with DNNs not being able to generalize well across different batches of histological slides, even when stain normalization techniques were applied.
  • The study emphasizes the urgent need for improved methods in preparing and standardizing microscopy images so that DNNs can effectively train and predict outcomes consistently across various datasets.
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Unlabelled: Using our recently developed laser speckle contrast imaging (LSCI) to visualize blood vessels and monitor blood flow, here we test the utility of the chick embryo for drug screening. To this end, we examined the effects of antihypertensive agents Nifedipine and Amlodipine, belonging to the L-type calcium channel antagonist family, on blood flow visualized noninvasively through the intact shell. Guided by the live view mode, the drugs were injected through the shell and ventral to HH16-19 chick embryos.

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Stroke poses a significant global health threat, with millions affected annually, leading to substantial morbidity and mortality. Current stroke risk assessment for the general population relies on markers such as demographics, blood tests, and comorbidities. A minimally invasive, clinically scalable, and cost-effective way to directly measure cerebral blood flow presents an opportunity.

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The characteristics of subvisible particles (SbVPs) are critical quality attributes of injectable and ophthalmic solutions in pharmaceutical manufacturing. However, current compendial SbVP testing methods, namely the light obstruction method and the microscopic particle count method, are destructive and wasteful of target samples. In this study, we present the development of a non-destructive SbVP analyzer aiming to analyze SbVPs directly in drug product (DP) containers while keeping the samples intact.

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Imaging three-dimensional microbial development and behavior over extended periods is crucial for advancing microbiological studies. Here, we introduce an upgraded ePetri dish system specifically designed for extended microbial culturing and 3D imaging, addressing the limitations of existing methods. Our approach includes a sealed growth chamber to enable long-term culturing, and a multi-step reconstruction algorithm that integrates 3D deconvolution, image filtering, ridge, and skeleton detection for detailed visualization of the hyphal network.

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Synthetic aperture radar (SAR) utilizes an aircraft-carried antenna to emit electromagnetic pulses and detect the returning echoes. As the aircraft travels across a designated area, it synthesizes a large virtual aperture to improve image resolution. Inspired by SAR, we introduce synthetic aperture ptycho-endoscopy (SAPE) for micro-endoscopic imaging beyond the diffraction limit.

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Computational imaging methods empower modern microscopes to produce high-resolution, large field-of-view, aberration-free images. Fourier ptychographic microscopy can increase the space-bandwidth product of conventional microscopy, but its iterative reconstruction methods are prone to parameter selection and tend to fail under excessive aberrations. Spatial Kramers-Kronig methods can analytically reconstruct complex fields, but is limited by aberration or providing extended resolution enhancement.

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Significance: In the realm of cerebrovascular monitoring, primary metrics typically include blood pressure, which influences cerebral blood flow (CBF) and is contingent upon vessel radius. Measuring CBF noninvasively poses a persistent challenge, primarily attributed to the difficulty of accessing and obtaining signal from the brain.

Aim: Our study aims to introduce a compact speckle contrast optical spectroscopy device for noninvasive CBF measurements at long source-to-detector distances, offering cost-effectiveness, and scalability while tracking blood flow (BF) with remarkable sensitivity and temporal resolution.

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Brain metastases can occur in nearly half of patients with early and locally advanced (stage I-III) non-small cell lung cancer (NSCLC). There are no reliable histopathologic or molecular means to identify those who are likely to develop brain metastases. We sought to determine if deep learning (DL) could be applied to routine H&E-stained primary tumor tissue sections from stage I-III NSCLC patients to predict the development of brain metastasis.

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In the realm of cerebrovascular monitoring, primary metrics typically include blood pressure, which influences cerebral blood flow (CBF) and is contingent upon vessel radius. Measuring CBF non-invasively poses a persistent challenge, primarily attributed to the difficulty of accessing and obtaining signal from the brain. This study aims to introduce a compact speckle visibility spectroscopy (SVS) device designed for non-invasive CBF measurements, offering cost-effectiveness and scalability while tracking CBF with remarkable sensitivity and temporal resolution.

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Recently, speckle visibility spectroscopy (SVS) was non-invasively applied on the head to monitor cerebral blood flow. The technique, using a multi-pixel detecting device (e.g.

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The emerging field of liquid biopsy stands at the forefront of novel diagnostic strategies for cancer and other diseases. Liquid biopsy allows minimally invasive molecular characterization of cancers for diagnosis, patient stratification to therapy, and longitudinal monitoring. Liquid biopsy strategies include detection and monitoring of circulating tumor cells, cell-free DNA, and extracellular vesicles.

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Diffusing wave spectroscopy (DWS) is a group of techniques used to measure the dynamics of a scattering medium in a non-invasive manner. DWS methods rely on detecting the speckle light field from the moving scattering medium and measuring the speckle decorrelation time to quantify the scattering medium's dynamics. For DWS, the signal-to-noise (SNR) is determined by the ratio between measured decorrelation time to the standard error of the measurement.

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Holography based on Kramers-Kronig relations (KKR) is a promising technique due to its high-space-bandwidth product. However, the absence of an iterative process limits its noise robustness, primarily stemming from the lack of a regularization constraint. This Letter reports a generalized framework aimed at enhancing the noise robustness of KKR holography.

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Circulating tumor cells (CTCs) and cancer-associated fibroblasts (CAFs) from whole blood are emerging as important biomarkers that potentially aid in cancer diagnosis and prognosis. The microfilter technology provides an efficient capture platform for them but is confounded by two challenges. First, uneven microfilter surfaces makes it hard for commercial scanners to obtain images with all cells in-focus.

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Context: Cytology is the study of whole cells in diagnostic pathology. Unlike standard histologic thinly sliced specimens, cytologic preparations consist of preparations of whole cells where cells commonly cluster and aggregate. As such, cytology preparations are generally much thicker than histologic slides, resulting in large patches of defocus when examined under the microscope.

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Over the past decade, the research field of Fourier Ptychographic Microscopy (FPM) has seen numerous innovative developments that significantly expands its utility. Here, we report a high numerical aperture (NA) FPM implementation that incorporates some of these innovations to achieve a synthetic NA of 1.9 - close to the maximum possible synthetic NA of 2 for a free space FPM system.

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This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.

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