The development of a robust 3D imaging system for underwater applications is a crucial process in underwater imaging where the physical properties of the underwater environment make the implementation of such systems challenging. Calibration is an essential step in the application of such imaging systems and is performed to acquire the parameters of the image formation model and to enable 3D reconstruction. We present a novel calibration method for an underwater 3D imaging system comprising a pair of cameras, of a projector, and of a single glass interface that is shared between cameras and projector(s). The image formation model is based on the axial camera model. The proposed calibration uses a numerical optimization of a 3D cost function to determine all system parameters, thus avoiding the minimization of re-projection errors which require numerically solving a 12th order polynomial equation multiple times for each observed point. We also propose a novel stable approach to estimate the axis of the axial camera model. The proposed calibration was experimentally evaluated on four different glass interfaces, wherein several quantitative results were reported, including the re-projection error. The achieved mean angular error of the system's axis was under 6∘, and the mean absolute errors for the reconstruction of a flat surface were 1.38 mm for normal glass interfaces and 2.82 mm for the laminated glass interface, which is more than sufficient for application.
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http://dx.doi.org/10.3390/s23125444 | DOI Listing |
J Neurosurg Case Lessons
January 2025
Neurosurgery Department, Palmetto General Hospital, Hialeah, Florida.
Background: Astroblastoma is an extremely rare tumor of the central nervous system, and its origin and validity as a different entity are still being debated. Because of its rarity and similarities to other glial neoplasms, it is often misdiagnosed, impacting treatment and outcomes.
Observations: Astroblastoma is very rare and mainly affects children and young adults.
Rheumatology (Oxford)
January 2025
Department of Medical Sciences, Surgery and Neurosciences, Research Center of Systemic Autoinflammatory Diseases and Behçet's Disease Clinic, University of Siena, Siena, Italy.
Objectives: To assess the lung involvement in patients with Still's disease, an inflammatory disease assessing both children and adults. To exploit possible associated factors for parenchymal lung involvement in these patients.
Methods: A multicentre observational study was arranged assessing consecutive patients with Still's disease characterized by the lung involvement among those included in the AIDA (AutoInflammatory Disease Alliance) Network Still's Disease Registry.
J Invasive Cardiol
January 2025
Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, China; State Key Laboratory of Cardiovascular Diseases, Zhongshan Hospital, Fudan University; NHC Key Laboratory of Ischemic Heart Diseases; Key Laboratory of Viral Heart Diseases, Chinese Academy of Medical Sciences; National Clinical Research Center for Interventional Medicine, Shanghai, China.
Objectives: The ValveClamp system (Hanyu Medical Technology) is a novel transcatheter edge-to-edge repair (TEER) system designed for ease of operation; however, there is a lack of data on its application in secondary mitral regurgitation (SMR). The authors report the mid-term outcomes of TEER using the ValveClamp system in SMR.
Methods: The study prospectively analyzed consecutive severe SMR patients who underwent transapical ValveClamp implantation at 10 Chinese centers.
Dentomaxillofac Radiol
January 2025
Division of Oral Radiology, Faculdade São Leopoldo Mandic.
Objectives: The aim of this technical report was to assess whether the "Radiological Report" tool within the Artificial Intelligence (AI) software Diagnocat can achieve a satisfactory level of performance comparable to that of experienced dentomaxillofacial radiologists in interpreting cone-beam CT scans.
Methods: Ten cone-beam CT scans were carefully selected and analyzed using the AI tool, and they were also evaluated by two dentomaxillofacial radiologists. Observations related to tooth numeration, alterations in dental crowns, roots, and periodontal tissues were documented and subsequently compared to the AI findings.
Dentomaxillofac Radiol
January 2025
Department of Oral and Maxillofacial Radiology, School of Dentistry, Pusan National University, Yangsan, 50612, Korea.
Objectives: This study aimed to develop an automated method for generating clearer, well-aligned panoramic views by creating an optimized three-dimensional (3D) reconstruction zone centered on the teeth. The approach focused on achieving high contrast and clarity in key dental features, including tooth roots, morphology, and periapical lesions, by applying a 3D U-Net deep learning model to generate an arch surface and align the panoramic view.
Methods: This retrospective study analyzed anonymized cone-beam CT (CBCT) scans from 312 patients (mean age 40 years; range 10-78; 41.
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