Ultrasound contrast-enhanced super-resolution imaging has recently attracted attention because of its extraordinary ability to image vascular features much smaller than the ultrasound diffraction limit. This method requires sensitive detection of separable microbubble events despite a noisy tissue background to indicate the microvasculature, and any approach that could improve the sensitivity of the ultrasound system to individual microbubbles would be highly beneficial. In this study, we evaluated the effect of varying microbubble size on super-resolution imaging sensitivity. Microbubble preparations were size sorted into different mean diameters and then were imaged at equal concentrations. Commercially manufactured Definity and Optison were also imaged for comparison. Both in vitro experiments in phantom vessels and in vivo experiments imaging rat tumors revealed that the sensitivity of contrast-enhanced super-resolution imaging can be improved by using microbubbles with a larger diameter.
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http://dx.doi.org/10.1016/j.ultrasmedbio.2017.05.014 | DOI Listing |
Sci Rep
December 2024
College of Jilin Emergency Management, Changchun Institute of Technology, Changchun, 130021, China.
This study focuses on the northern scenic area of Changbai Mountain, aiming to evaluate the emergency evacuation capacity of the region in the context of geological disasters and to formulate corresponding improvement strategies. Due to the relatively small area of this region, difficulties in data acquisition, and insufficient precision, traditional models for evaluating emergency evacuation capacity are typically applied to urban built environments, with relatively few studies addressing scenic areas. To tackle these issues, this research employs the Real-Enhanced Super-Resolution Generative Adversarial Network (Real-ESRGAN), which successfully resolves the problem of blurriness in remote sensing images and significantly enhances image clarity.
View Article and Find Full Text PDFCell Rep Methods
December 2024
Portrai, Inc., Dongsullagil, 78-18 Jongrogu, Seoul, Republic of Korea; Department of Nuclear Medicine, Seoul National University Hospital, 03080 Seoul, Republic of Korea; Department of Nuclear Medicine, Seoul National University College of Medicine, 03080 Seoul, Republic of Korea. Electronic address:
Spatially resolved transcriptomics (ST) has revolutionized the field of biology by providing a powerful tool for analyzing gene expression in situ. However, current ST methods, particularly barcode-based methods, have limitations in reconstructing high-resolution images from barcodes sparsely distributed in slides. Here, we present SuperST, an algorithm that enables the reconstruction of dense matrices (higher-resolution and non-zero-inflated matrices) from low-resolution ST libraries.
View Article and Find Full Text PDFEBioMedicine
December 2024
Physics for Medicine Paris, INSERM U1273, ESPCI Paris, CNRS UMR 8063, PSL Research University, Paris, France.
Background: Neovascularisation of carotid plaques contributes to their vulnerability. Current imaging methods such as contrast-enhanced ultrasound (CEUS) usually lack the required spatial resolution and quantification capability for precise neovessels identification. We aimed at quantifying plaque vascularisation with ultrasound localization microscopy (ULM) and compared the results to histological analysis.
View Article and Find Full Text PDFBiomimetics (Basel)
December 2024
School of Computer Information and Engineering, Nanchang Institute of Technology, Nanchang 330044, China.
Image super-resolution (SR) is a formidable challenge due to the intricacies of the underwater environment such as light absorption, scattering, and color distortion. Plenty of deep learning methods have provided a substantial performance boost for SR. Nevertheless, these methods are not only computationally expensive but also often lack flexibility in adapting to severely degraded image statistics.
View Article and Find Full Text PDFIEEE Access
November 2024
University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
The achievable spatial resolution of C metabolic images acquired with hyperpolarized C-pyruvate is worse than H images typically by an order of magnitude due to the rapidly decaying hyperpolarized signals and the low gyromagnetic ratio of C. This study is to develop and characterize a volumetric patch-based super-resolution reconstruction algorithm that enhances spatial resolution C cardiac MRI by utilizing structural information from H MRI. The reconstruction procedure comprises anatomical segmentation from high-resolution H MRI, calculation of a patch-based weight matrix, and iterative reconstruction of high-resolution multi-slice C MRI.
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