Magnetic Resonance Imaging and x-ray Computed Tomography have limitations when applied to diseases of the human inner ear due to insufficient resolution. Key morphological features of the inner ear are below the resol...
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ISBN:
(纸本)9781510669208;9781510669192
Magnetic Resonance Imaging and x-ray Computed Tomography have limitations when applied to diseases of the human inner ear due to insufficient resolution. Key morphological features of the inner ear are below the resolving power of both modalities;thus, they are unable to measure functional aspects of the microstructures in the cochlea. Furthermore, general access to the cochlea is a challenge due to its location in the inner ear and its bony encapsulation. These limitations cause clinicians to rely on clinical history when diagnosing and managing hearing loss in patients, which is not ideal. This paper explores the application of Optical Coherence Tomography (OCT) as a diagnostic tool for inner ear diseases. OCT's high spatial and temporal resolution allows for detailed imaging of inner ear structures and their function. To address the challenge of accessing the cochlea in humans, a hand-held endoscopic OCT device has been developed that can image through the round window membrane. The technology has been tested in cadaver temporal bone, enabling functional and morphological imaging of the cochlea when navigated to the round window. Alongside the device, we are developing an algorithm to perform subsequent stitching of volumes to overcome limitations with a small field of view. Applying this algorithm on cadaver tissue serves as a preliminary step before advancing to live human cochlear imaging. By utilizing our hand-held OCT endoscope, clinicians will have the ability to record changes in morphological and functional information, thereby improving the approach to diagnosing and treating patients with inner ear diseases.
In this work, an intelligent monitoring method based on target detection and pose estimation is proposed for personal protective equipment monitoring and deep analysis of safety behavior. Different from previous image...
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In support of the detection of explosives and threat chemicals by active infrared backscatter hyperspectral imaging, we are training algorithms to process and alert on possible threats. Surfaces are interrogated using...
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ISBN:
(纸本)9781510673816;9781510673809
In support of the detection of explosives and threat chemicals by active infrared backscatter hyperspectral imaging, we are training algorithms to process and alert on possible threats. Surfaces are interrogated using infrared quantum cascade lasers (QCL) and the backscattered signal is collected using a cooled MCT focal plane array (FPA). The QCLs can tune across their full wavelength range, from 6 - 11 mu m, in less than one second. Full 128 X 128 pixel frames from the FPA are collected and compiled into a hyperspectral image (HSI) cube containing spectral and spatial information from the target. The HSI cubes are processed and the spectra from extracted pixel locations are then run through an algorithm to detect and identify traces of explosives. We train our algorithms on both synthetic and experimental data. In this presentation, we utilize machine learning algorithms to classify HSI cubes from a series of targets coupons fabricated on relevant substrates (glass, painted metal, plastics, cardboard). We explain how the algorithm training uses reference spectral measurements from our cart system as well as from a benchtop FTIR. The generation and utility of synthetic data is described regarding how we populate the algorithms' spectral library more densely than would be possible using only measured experimental data. The performance of several ML algorithms is described.
In response to issues of low detection accuracy and poor robustness caused by missed detections of small objects and occlusions among dense objects in road scenes, a YOLOv8-RC object detection algorithm is proposed. F...
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The P-U characteristic curves of PV arrays under localized shading conditions may exhibit multiple peaks. Conventional approaches are prone to encountering the local maximum power point (LMPP) and face challenges in e...
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The Simons Observatory (SO) is a ground-based cosmic microwave background experiment currently being deployed to Cerro Toco in the Atacama Desert of Chile. The initial deployment of SO, consisting of three 0.46mdiamet...
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ISBN:
(纸本)9781510675261;9781510675254
The Simons Observatory (SO) is a ground-based cosmic microwave background experiment currently being deployed to Cerro Toco in the Atacama Desert of Chile. The initial deployment of SO, consisting of three 0.46mdiameter small-aperture telescopes and one 6m-primary large-aperture telescope, will field over 60,000 transitionedge sensors that will observe at frequencies between 30 GHz and 280 GHz. SO will read out its detectors using Superconducting Quantum Interference Device (SQUID) microwave-frequency multiplexing (mu mux), a form of frequency division multiplexing where an RF-SQUID couples each TES bolometer to a superconducting resonator tuned to a unique frequency. Resonator frequencies are spaced roughly every 2 MHz between 4 and 6 GHz, allowing for multiplexing factors on the order of 1000. One challenge of mu mux is matching each tracked resonator with its corresponding physical detector. Variations in resonator fabrication, and frequency shifts between cooldowns caused by trapped flux can cause the measured resonance frequencies to deviate significantly from their designed values. In this study, we introduce a method for pairing measured and designed resonators by constructing a bipartite graph based on the two resonator sets, and assigning edge weights based on measured resonator and detector properties such as resonance frequency, detector pointing, and assigned bias lines. Finding the minimum-cost matching for a given set of edge weights is a well-studied problem that can be solved very quickly, and this matching tells us the best assignment of measured resonators to designed detectors for our input parameters. We will present results based on the first on-sky measurements from SAT1, the first SO MF small-aperture telescope.
In order to realize the detection problem of whether the goods package has been opened by intelligent forklift in warehousing and logistics, an object detection algorithm SSA-YOLOv5n based on improved YOLOv5n is propo...
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In recent years, location-based services have gradually penetrated all aspects of people's daily life, bringing great convenience to people's work and life. Pedestrian Dead Reckoning (PDR) is a positioning met...
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Soybean protein is one of the important components of modern human diet. How to accurately and quickly determine the location of soybean protein is the main topic of research scholars. In order to understand the soybe...
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The accurate identification of large and medium slag in power plant slag transport system has an important impact on the safety, efficiency, environmental protection and economic benefits of power plant. The timely pr...
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