Corrections to the published article include values in Table 1 and provision of an omitted reference.
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http://dx.doi.org/10.1117/1.JBO.27.5.059801 | DOI Listing |
Sensors (Basel)
December 2024
CeMOS Research and Transfer Center, Mannheim University of Applied Sciences, 68163 Mannheim, Germany.
Advancements in Raman light sheet microscopy have provided a powerful, non-invasive, marker-free method for imaging complex 3D biological structures, such as cell cultures and spheroids. By combining 3D tomograms made by Rayleigh scattering, Raman scattering, and fluorescence detection, this modality captures complementary spatial and molecular data, critical for biomedical research, histology, and drug discovery. Despite its capabilities, Raman light sheet microscopy faces inherent limitations, including low signal intensity, high noise levels, and restricted spatial resolution, which impede the visualization of fine subcellular structures.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Information Technology, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India.
Hyperspectral remote sensing images obtained from cameras are characterized by high-dimensions and low quality, which makes them unfavorable for various analytics purposes. This is due to the presence of visible and invisible frequencies of the reflected light making it poorly reveal the spectral signatures of the image. Visual communication advancement has paved the need for Image Super-Resolution (SR) which recovers high-resolution images from low-resolution images.
View Article and Find Full Text PDFCurr Med Imaging
November 2024
Division of Pediatric Cardiology, Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, USA.
Background: Three-dimensional (3D) whole-heart magnetic resonance imaging (MRI) is an excellent tool to check the heart anatomy of patients with congenital and acquired heart disease. However, most 3D whole-heart MRI acquisitions take a long time to perform, and the sequence used is susceptible to banding artifacts.
Purpose: To validate an unsupervised neural network that can reduce acquisition time and improve image quality for 3D whole-heart MRI by superresolving low-resolution images.
J Med Imaging (Bellingham)
November 2024
Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States.
Purpose: Eye morphology varies significantly across the population, especially for the orbit and optic nerve. These variations limit the feasibility and robustness of generalizing population-wise features of eye organs to an unbiased spatial reference.
Approach: To tackle these limitations, we propose a process for creating high-resolution unbiased eye atlases.
Sensors (Basel)
November 2024
CeMOS Research and Transfer Center, University of Applied Science, 68163 Mannheim, Germany.
This study presents an advanced integration of Multi-modal Raman Light Sheet Microscopy with zero-shot learning-based computational methods to significantly enhance the resolution and analysis of complex three-dimensional biological structures, such as 3D cell cultures and spheroids. The Multi-modal Raman Light Sheet Microscopy system incorporates Rayleigh scattering, Raman scattering, and fluorescence detection, enabling comprehensive, marker-free imaging of cellular architecture. These diverse modalities offer detailed spatial and molecular insights into cellular organization and interactions, critical for applications in biomedical research, drug discovery, and histological studies.
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