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Exposure therapy is an efficacious treatment for anxiety-related disorders. Yet, fear often returns after treatment. Occasional reinforcement, in which the feared stimulus is intermittently presented during extinction, increases safety learning and slows fear renewal in conditioning paradigms and analogue samples, but no studies to date have examined this strategy in clinical samples.

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We describe a novel application of photon-counting detector CT (PCD-CT) in neurovascular imaging by harnessing the improved spatial resolution, attenuation of electronic noise, and reduction of metal artifacts. The presented case offers the unique challenge of high-quality imaging for the assessment of treated and untreated intracranial saccular aneurysms, in the setting of metal artifacts from embolization coils. Our goal was to explore optimized reconstruction parameters for ultra-high-resolution imaging (UHR) using a dedicated, sharp neurovascular kernel (Hv72) and the highest strength of quantum iterative reconstruction (QIR-4) for detailed characterization of the vasculature.

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Background/context: Chronic low back pain (CLBP) is a significant US healthcare burden with millions of lumbar spine procedures annually. Diagnostic tests are essential to guide treatment but provocative discography (PD), the most common diagnostic procedure, is without robust evidence of its value. A non-invasive alternative using Magnetic Resonance Spectroscopy (MRS) offers a potential solution.

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MITIGATING OVER-SATURATED FLUORESCENCE IMAGES THROUGH A SEMI-SUPERVISED GENERATIVE ADVERSARIAL NETWORK.

Proc IEEE Int Symp Biomed Imaging

May 2024

Department of Electrical and Computer Engineering, Nashville, TN, USA.

Multiplex immunofluorescence (MxIF) imaging is a critical tool in biomedical research, offering detailed insights into cell composition and spatial context. As an example, DAPI staining identifies cell nuclei, while CD20 staining helps segment cell membranes in MxIF. However, a persistent challenge in MxIF is saturation artifacts, which hinder single-cell level analysis in areas with over-saturated pixels.

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