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Scanner-based real-time three-dimensional brain + body slice-to-volume reconstruction for T2-weighted 0.55-T low-field fetal magnetic resonance imaging.
Pediatr Radiol
January 2025
Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, SE1 7EH, UK.
Background: Motion correction methods based on slice-to-volume registration (SVR) for fetal magnetic resonance imaging (MRI) allow reconstruction of three-dimensional (3-D) isotropic images of the fetal brain and body. However, all existing SVR methods are confined to research settings, which limits clinical integration. Furthermore, there have been no reported SVR solutions for low-field 0.
View Article and Find Full Text PDFLeft ventricular rigor mortis interferes with postmortem aortic root geometry.
Int J Legal Med
January 2025
Institute for Legal Medicine, Faculty of Medicine, Saarland University, Campus Homburg, Building 49.1, Kirrberger Straße 100, 66421, Homburg/Saar, Germany.
Aortic regurgitation is a common valve disease and can be caused by delineated findings such as fenestrations or hardly discernible alterations of the aortic root geometry. Therefore, aortic regurgitation can be a challenging diagnosis during an autopsy. Cardiac surgeons, however, are confronted with comparable problems during surgery and have developed a refined knowledge of the anatomy of the aortic root including its geometry.
View Article and Find Full Text PDFInterobserver reliability of Pirani scoring for idiopathic clubfoot in walking-age children.
J Pediatr Orthop B
January 2025
Department of Paediatric Orthopaedics, Chacha Nehru Bal Chikitsalaya, Delhi, India.
Pirani scoring system is one of the most commonly used tools to assess the initial deformity, monitor the treatment progression, and identify relapse in clubfoot. The method has been demonstrated to correlate well with the sequential correction of deformity for children under age 1 year. We conducted a study to examine the interobserver reliability of Pirani scores in children of walking-age.
View Article and Find Full Text PDFLearning-based motion artifact correction in the Z-spectral domain for chemical exchange saturation transfer MRI.
Magn Reson Med
January 2025
Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA.
Purpose: To develop and evaluate a physics-driven, saturation contrast-aware, deep-learning-based framework for motion artifact correction in CEST MRI.
Methods: A neural network was designed to correct motion artifacts directly from a Z-spectrum frequency (Ω) domain rather than an image spatial domain. Motion artifacts were simulated by modeling 3D rigid-body motion and readout-related motion during k-space sampling.
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