A high-speed ultra-wideband microwave spectral scanning system is proposed and experimentally demonstrated. Utilizing coherent dual electro-optical frequency combs and a recirculating optical frequency shifter, the proposed system realizes wavelength- and time-division multiplexing at the same time, offering flexibility between scan speed and size, weight and power requirements (SWaP). High-speed spectral scanning spanning from ~1 to 8 GHz with ~1.2 MHz spectral resolution is achieved experimentally within 14 µs. The system can be easily scaled to higher bandwidth coverage, faster scanning speed or finer spectral resolution with suitable hardware.
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http://dx.doi.org/10.1364/OE.25.018863 | DOI Listing |
Transl Vis Sci Technol
January 2025
New England Eye Center, Tufts Medical Center, Boston, MA, USA.
Purpose: To evaluate visibility of a sub-band posterior to the external limiting membrane (ELM) and assess its age-associated variation.
Methods: In a retrospective cross-sectional study, normal eyes were imaged using a high-resolution spectral-domain optical coherence tomography (SD-OCT) prototype (2.7-µm axial resolution).
Radiol Artif Intell
January 2025
From the Department of Radiation Oncology (A.S.G., V.H., H.S.) and Department of Radiology and Imaging Sciences (B.D.W.), Emory University School of Medicine, 1701 Uppergate Dr, C5008 Winship Cancer Institute, Atlanta, GA 30322; Department of Radiology, University of Miami {School of Medicine?}, Miami, Fla (S.S., A.A.M.); Department of {Radiology?} Northwestern University {Feinberg School of Medicine?}, Chicago, Ill (L.A.D.C.); Department of Biostatistics and Bioinformatics, Emory University Rollins School of Public Health, Atlanta, Ga (Y.L.); Department of Psychology, Emory University, Atlanta, Ga (M.T.); and Department of Radiology, Duke University Medical Center, Durham, NC (B.J.S.).
Purpose To develop and evaluate the performance of NNFit, a self-supervised deep-learning method for quantification of high-resolution short echo-time (TE) echo-planar spectroscopic imaging (EPSI) datasets, with the goal of addressing the computational bottleneck of conventional spectral quantification methods in the clinical workflow. Materials and Methods This retrospective study included 89 short-TE whole-brain EPSI/GRAPPA scans from clinical trials for glioblastoma (Trial 1, May 2014-October 2018) and major-depressive-disorder (Trial 2, 2022- 2023). The training dataset included 685k spectra from 20 participants (60 scans) in Trial 1.
View Article and Find Full Text PDFData Brief
February 2025
Woodwell Climate Research Center, 149 Woods Hole Rd., Falmouth, MA, 02540, United States.
This near-infrared spectral dataset consists of 2,106 diverse mineral soil samples scanned, on average, on six different units of the same low-cost commercially available handheld spectrophotometer. Most soil samples were selected from the USDA NRCS National Soil Survey Center-Kellogg Soil Survey Laboratory (NSSC-KSSL) soil archives to represent the diversity of mineral soils (0-30 cm) found in the United States, while 90 samples were selected from Ghana, Kenya, and Nigeria to represent available African soils in the same archive. All scanning was performed on dried and sieved (<2 mm) soil samples.
View Article and Find Full Text PDFComput Methods Programs Biomed
January 2025
Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Nanjing, China; School of Computer Science and Engineering, Southeast University, Nanjing, China.
Purpose: Dual-energy computed tomography (DECT) enables the differentiation of different materials. Additionally, DECT images consist of multiple scans of the same sample, revealing information similarity within the energy domain. To leverage this information similarity and address safety concerns related to excessive radiation exposure in DECT imaging, sparse view DECT imaging is proposed as a solution.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Department of Biology, University at Albany, SUNY, 1400 Washington Ave, Albany, NY 12222, United States.
The accuracy of assigning fluorophore identity and abundance, known as spectral unmixing, in biological fluorescence microscopy images remains a significant challenge due to the substantial overlap in emission spectra among fluorophores. In traditional laser scanning confocal spectral microscopy, fluorophore information is acquired by recording emission spectra with a single combination of discrete excitation wavelengths. However, organic fluorophores possess characteristic excitation spectra in addition to their unique emission spectral signatures.
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