A fiber-based snapshot imaging spectrometer was developed with a maximum of 31853 (~188 x 170) spatial sampling and 61 spectral channels in the 450nm-750nm range. A compact, custom-fabricated fiber bundle was used to sample the object image at the input and create void spaces between rows at the output for dispersion. The bundle was built using multicore 6x6 fiber block ribbons. To avoid overlap between the cores in the direction of dispersion, we selected a subset of cores using two alternative approaches; a lenslet array and a photomask. To calibrate the >30000 spatial samples of the system, a rapid spatial calibration method was developed based on phase-shifting interferometry (PSI). System crosstalk and spectral resolution were also characterized. Preliminary hyperspectral imaging results of the Rice University campus landscape, obtained with the spectrometer, are presented to demonstrate the system's spectral imaging capability for distant scenes. The spectrum of different plant species with different health conditions, obtained with the spectrometer, was in accordance with reference instrument measurements. We also imaged Houston traffic to demonstrate the system's snapshot hyperspectral imaging capability. Potential applications of the system include terrestrial monitoring, land use, air pollution, water resources, and lightning spectroscopy. The fiber-based system design potentially allows tuning between spatial and spectral sampling to meet specific imaging requirements.
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http://dx.doi.org/10.1364/OE.27.015701 | DOI Listing |
Eur J Radiol
December 2024
Division of Endocrinology and Metabolism, Department of Medicine III, Medical University of Vienna, Austria.
Objectives: To explore texture analysis' ability on T and T relaxation maps to classify liver fibrosis into no-to-mild liver fibrosis (nmF) versus severe fibrosis (sF) group using machine learning algorithms and histology as reference standard.
Materials And Methods: In this single-center study, patients undergoing 3 T MRI who also had histology examination were retrospectively enrolled. SNAPSHOT-FLASH sequence for T1 mapping, radial turbo-spin-echo sequence for T2 mapping and spin-echo echo-planar-imaging magnetic resonance elastography (MRE) sequences were analyzed.
Magn Reson Med
December 2024
Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.
Purpose: To implement and evaluate the feasibility of brain spin-lattice relaxation in the rotating frame (T1ρ) mapping using a novel optimized pulse sequence that incorporates weighted spin-lock acquisitions, enabling high-resolution three-dimensional (3D) mapping.
Methods: The optimized variable flip-angle framework, previously proposed for knee T1ρ mapping, was enhanced by integrating weighted spin-lock acquisitions. This strategic combination significantly boosts signal-to-noise ratio (SNR) while reducing data acquisition time, facilitating high-resolution 3D-T1ρ mapping of the brain.
Med Image Anal
December 2024
Department of Mathematics, University of California Irvine, USA; Department of Biomedical Engineering, University of California Irvine, USA. Electronic address:
Predicting the infiltration of Glioblastoma (GBM) from medical MRI scans is crucial for understanding tumor growth dynamics and designing personalized radiotherapy treatment plans. Mathematical models of GBM growth can complement the data in the prediction of spatial distributions of tumor cells. However, this requires estimating patient-specific parameters of the model from clinical data, which is a challenging inverse problem due to limited temporal data and the limited time between imaging and diagnosis.
View Article and Find Full Text PDFAlzheimers Res Ther
December 2024
Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Background: Posterior Cortical Atrophy (PCA) is a clinical syndrome characterized by progressive visuospatial and visuoperceptual impairment. As the neurodegenerative disease progresses, patients lose independent functioning due to the worsening of initial symptoms and development of symptoms in other cognitive domains. The timeline of clinical progression is variable across patients, and the field currently lacks robust methods for prognostication.
View Article and Find Full Text PDFSensors (Basel)
November 2024
Key Laboratory of Space Active Opto-Electronics Technology, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China.
Long-wave infrared (LWIR) spectral imaging plays a critical role in various applications such as gas monitoring, mineral exploration, and fire detection. Recent advancements in computational spectral imaging, powered by advanced algorithms, have enabled the acquisition of high-quality spectral images in real time, such as with the Uncooled Snapshot Infrared Spectrometer (USIRS). However, the USIRS system faces challenges, particularly a low spectral resolution and large amount of data noise, which can degrade the image quality.
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