Purpose: The aim of this study was to demonstrate the feasibility of building a craniofacial virtual reality model by image fusion of 3-dimensional (3D) CT models and 3 dMD stereophotogrammetric facial surface.
Methods: A CT scan and stereophotography were performed. The 3D CT models were reconstructed by Materialise Mimics software, and the stereophotogrammetric facial surface was reconstructed by 3 dMD patient software. All 3D CT models were exported as Stereo Lithography file format, and the 3 dMD model was exported as Virtual Reality Modeling Language file format. Image registration and fusion were performed in Mimics software. Genetic algorithm was used for precise image fusion alignment with minimum error. The 3D CT models and the 3 dMD stereophotogrammetric facial surface were finally merged into a single file and displayed using Deep Exploration software. Errors between the CT soft tissue model and 3 dMD facial surface were also analyzed.
Results: Virtual model based on CT-3 dMD image fusion clearly showed the photorealistic face and bone structures. Image registration errors in virtual face are mainly located in bilateral cheeks and eyeballs, and the errors are more than 1.5 mm. However, the image fusion of whole point cloud sets of CT and 3 dMD is acceptable with a minimum error that is less than 1 mm.
Conclusions: The ease of use and high reliability of CT-3 dMD image fusion allows the 3D virtual head to be an accurate, realistic, and widespread tool, and has a great benefit to virtual face model.
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http://dx.doi.org/10.1097/SCS.0b013e3182688ed7 | DOI Listing |
BMC Health Serv Res
January 2025
The University of Sydney, Faculty of Medicine and Health, School of Rural Health, Orange, NSW, 2800, Australia.
Background: Low-value care refers to the provision of health services that confer little or no benefit to patients, or have the potential to incur unwarranted harms. A breadth of literature exists investigating geographical variations in rates of potential low-value interventions for musculoskeletal pain. This scoping review aimed to examine the provision of low-value care for osteoarthritis and lower back pain by degree of rurality (e.
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January 2025
Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI, USA.
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View Article and Find Full Text PDFMethods Mol Biol
January 2025
AIBioMed Research Group, Taipei Medical University, Taipei, Taiwan.
SNARE proteins play a pivotal role in membrane fusion and various cellular processes. Accurate identification of SNARE proteins is crucial for elucidating their functions in both health and disease contexts. This chapter presents a novel approach employing multiscan convolutional neural networks (CNNs) combined with position-specific scoring matrix (PSSM) profiles to accurately recognize SNARE proteins.
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January 2025
Mechanical Engineering Department, Tianjin University, No. 135, Yaguan Road, Haihe Education Park, Jinnan District, Tianjin City, 300350, China.
The use of AR technology in image-guided neurosurgery enables visualization of lesions that are concealed deep within the brain. Accurate AR registration is required to precisely match virtual lesions with anatomical structures displayed under a microscope. The purpose of this work was to develop a real-time augmented surgical navigation system using contactless line-structured light registration, microscope calibration, and visible optical tracking.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Otorhinolaryngology - Head and Neck Surgery, University of Helsinki and Helsinki University Hospital, P.O. Box 263, 00029, Helsinki, Finland.
Three-dimensional (3D) modeling is often used to provide better visual understanding. This has become an everyday tool especially in medical imaging. However, modeling soft tissue histopathology in 3D is in its early stages, thus making 3D comparison between radiology and histopathology difficult.
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