Purpose: In order to measure spatial resolution of a PET tomograph in clinical conditions, this study describes and validates a method based on the recovery coefficient, a factor required to compensate underestimation in measured radioactivity concentration for small structures.
Methods: In a PET image, the recovery factors of radioactive spheres were measured and their comparison with simulated recovery coefficients yielded the tomographic spatial resolution. Following this methodology, resolution was determined in different surrounding media and several conditions for reconstruction, including clinical conditions for brain PET studies. All spatial resolution values were compared with those obtained using classical methods with point and line sources.
Results: In each considered condition, spatial resolution of the PET image estimated using the recovery coefficient showed good agreement with classical methods measurements, validating the procedure.
Conclusion: Measurement of the recovery coefficient provides an assessment of tomographic spatial resolution, particularly in clinical studies conditions.
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http://dx.doi.org/10.1016/j.compbiomed.2009.11.002 | DOI Listing |
Proc Natl Acad Sci U S A
January 2025
School of Politics and Public Administration, Soochow University, Suzhou 215006, China.
Urban vegetation provides essential ecosystem services and benefits to support biodiversity and human well-being in urban areas. However, the dynamic trends, driving factors, and their implications to urban heat mitigation at the global scale remain largely unclear. Here, we used a high-resolution enhanced vegetation index (EVI) dataset to examine the vegetation dynamics in 11,235 urban areas worldwide, identify the driving factors behind its changes, and estimate the potential urban heat mitigation benefits of these changes.
View Article and Find Full Text PDFAnal Methods
January 2025
International Research Centre for Nano Handling and Manufacturing of China, Changchun University of Science and Technology, Changchun 130022, China.
Atomic force microscopy (AFM) is widely used for the imaging and characterization of biological cells because of its nanoscale spatial resolution and force resolution. However, in the previous studies, the inability to effectively detect the contractile work of cardiomyocytes and the 3D dynamic expressions of their contraction and relaxation behaviors posed significant challenges. Therefore, this work presents a method for the analysis of the contractile work of a single cardiomyocyte by AFM.
View Article and Find Full Text PDFFront Neurosci
January 2025
Functional Magnetic Resonance Imaging (FMRI) Core, NIH, National Institute of Mental Health, Bethesda, MD, United States.
The use of submillimeter resolution functional magnetic resonance imaging (fMRI) is increasing in popularity due to the prospect of studying human brain activation non-invasively at the scale of cortical layers and columns. This method, known as laminar fMRI, is inherently signal-to-noise ratio (SNR)-limited, especially at lower field strengths, with the dominant noise source being of thermal origin. Furthermore, laminar fMRI is challenged with signal displacements due to draining vein effects in conventional gradient-echo blood oxygen level-dependent (BOLD) imaging contrasts.
View Article and Find Full Text PDFData Brief
February 2025
Tecnológico Nacional de México/Instituto Tecnológico de Culiacán, División de Estudios de Posgrado e Investigación, Juan de Dios Batíz 310. Col. Guadalupe, 80220 Culiacán, Sinaloa, Mexico.
A dataset of aerial photographs acquired with an Unmanned Aerial Vehicle (UAV) DJI Phantom 4 Pro is presented for monitoring a cherry tomato ( var. ) crop in Navolato, Mexico. Seven photogrammetric flights were carried out to assess the plant growth using a Mapir Survey 3W multispectral camera.
View Article and Find Full Text PDFBMC Genomics
January 2025
UCLA Technology Center for Genomics & Bioinformatics, Department of Pathology & Laboratory Medicine, 650 Charles E Young Dr. South, Los Angeles, CA, 90095, USA.
Spatial transcriptomics technology enables the mapping of gene expression within tissues, allowing researchers to visualize the spatial distribution of RNA molecules and gain insights into cellular organization, interactions, and functions in their native environments. A variety of spatial technologies are now commercially available, each offering distinct technical parameters such as cellular resolution, detection sensitivity, gene coverage, and throughput. This wide range of options can make it challenges or create confusion for researchers to select the most appropriate platform for their specific research objectives.
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