Split-blade diffusion-weighted periodically rotated overlapping parallel lines with enhanced reconstruction (DW-PROPELLER) was proposed to address the issues associated with diffusion-weighted echo planar imaging such as geometric distortion and difficulty in high-resolution imaging. The major drawbacks with DW-PROPELLER are its high SAR (especially at 3T) and violation of the Carr-Purcell-Meiboom-Gill condition, which leads to a long scan time and narrow blade. Parallel imaging can reduce scan time and increase blade width; however, it is very challenging to apply standard k-space-based techniques such as GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) to split-blade DW-PROPELLER due to its narrow blade. In this work, a new calibration scheme is proposed for k-space-based parallel imaging method without the need of additional calibration data, which results in a wider, more stable blade. The in vivo results show that this technique is very promising.
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http://dx.doi.org/10.1002/mrm.22646 | DOI Listing |
Am J Orthod Dentofacial Orthop
January 2025
Department of Orthodontics, Faculty of Dentistry, Hacettepe University, Ankara, Turkey. Electronic address:
Introduction: The objective of this study was to evaluate the effects of the miniplate application sites in the maxilla and the applied force vector changes during skeletally supported facemask application in adolescent patients with unilateral cleft lip and palate (UCLP) using finite element model (FEM) analysis.
Methods: A FEM was obtained from a cone-beam computed tomography image of a 12-year-old female patient with UCLP. Miniplates were placed on 3 different sites of the maxilla; 500 g of advancement force was applied bilaterally, parallel (0°), and downward (-30°) to the occlusal plane.
BMJ Open Gastroenterol
December 2024
Australian Centre for Health Services Innovation, Centre for Healthcare Transformation, School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Kelvin Grove, Queensland, Australia
Objective: Non-alcoholic fatty liver disease (NAFLD) is estimated to affect a third of Australian adults, and its prevalence is predicted to rise, increasing the burden on the healthcare system. The LOCal Assessment and Triage Evaluation of Non-Alcoholic Fatty Liver Disease (LOCATE-NAFLD) trialled a community-based fibrosis assessment service using FibroScan to reduce the time to diagnosis of high-risk NAFLD and improve patient outcomes.
Methods: We conducted a 1:1 parallel randomised trial to compare two alternative models of care for NAFLD diagnosis and assessment.
Sensors (Basel)
January 2025
Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy.
The increasing demand for hazelnut kernels is favoring an upsurge in hazelnut cultivation worldwide, but ongoing climate change threatens this crop, affecting yield decreases and subject to uncontrolled pathogen and parasite attacks. Technical advances in precision agriculture are expected to support farmers to more efficiently control the physio-pathological status of crops. Here, we report a straightforward approach to monitoring hazelnut trees in an open field, using aerial multispectral pictures taken by drones.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Applied Physics, National Defense Academy, Hashirimizu 1-10-20, Yokosuka 239-0802, Kanagawa, Japan.
Dielectrophoresis (DEP) cell separation technology is an effective means of separating target cells which are only marginally present in a wide variety of cells. To develop highly efficient cell separation devices, detailed analysis of the nonuniform electric field's intensity distribution within the device is needed, as it affects separation performance. Here we analytically expressed the distributions of the electric field and DEP force in a parallel-plate cell separation DEP device by employing electrostatic analysis through the Fourier series method.
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December 2024
School of Physics and Electronics, Nanning Normal University, Nanning 530100, China.
Remote sensing change detection (RSCD), which utilizes dual-temporal images to predict change locations, plays an essential role in long-term Earth observation missions. Although many deep learning based RSCD models perform well, challenges remain in effectively extracting change information between dual-temporal images and fully leveraging interactions between their feature maps. To address these challenges, a constraint- and interaction-based network (CINet) for RSCD is proposed.
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