Background: The vertebral artery (VA) has a tortuous course subdivided into 4 segments (V1-V4). For neurosurgeons, a thorough knowledge of the 3-dimensional (3D) anatomy at different segments is a prerequisite for safe surgery. New technologies allowing creation of photorealistic 3D models may enhance the anatomic understanding of this complex region.
Objective: To create photorealistic 3D models illustrating the anatomy and surgical steps needed for safe neurosurgical exposure of the VA.
Methods: We dissected 2 latex injected cadaver heads. Anatomic layered dissections were performed on the first specimen. On the second specimen, the two classical approaches to the VA (far lateral and anterolateral) were realized. Every step of dissection was scanned using photogrammetry technology that allowed processing of 3D data from 2-dimensional photographs by a simplified algorithm mainly based on a dedicated mobile phone application and open-source 3D modeling software. For selected microscopic 3D anatomy, we used an operating microscope to generate 3D models.
Results: Classic anatomic (n=17) and microsurgical (n=12) 3D photorealistic models based on cadaver dissections were created. The models allow observation of the spatial relations of each anatomic structure of interest and have an immersive view of the approaches to the V2-V4 segments of the VA. Once generated, these models may easily be shared on any digital device or web-based platforms for 3D visualization.
Conclusions: Photorealistic 3D scanning technology is a promising tool to present complex anatomy in a more comprehensive way. These 3D models can be used for education, training, and potentially preoperative planning.
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http://dx.doi.org/10.1227/ons.0000000000000701 | DOI Listing |
Eur J Hum Genet
January 2025
Institute for Genomic Statistics and Bioinformatics, Bonn, NRW, Germany.
The facial gestalt (overall facial morphology) is a characteristic clinical feature in many genetic disorders that is often essential for suspecting and establishing a specific diagnosis. Therefore, publishing images of individuals affected by pathogenic variants in disease-associated genes has been an important part of scientific communication. Furthermore, medical imaging data is also crucial for teaching and training deep-learning models such as GestaltMatcher.
View Article and Find Full Text PDFNeural Netw
January 2025
School of Automation Science and Engineering, South China University of Technology, China. Electronic address:
Talking face generation is a promising approach within various domains, such as digital assistants, video editing, and virtual video conferences. Previous works with audio-driven talking faces focused primarily on the synchronization between audio and video. However, existing methods still have certain limitations in synthesizing photo-realistic video with high identity preservation, audiovisual synchronization, and facial details like blink movements.
View Article and Find Full Text PDFJ Imaging
December 2024
Department of Computer Science, Kiel University, 24118 Kiel, Germany.
Due to recent advances in 3D reconstruction from RGB images, it is now possible to create photorealistic representations of real-world scenes that only require minutes to be reconstructed and can be rendered in real time. In particular, 3D Gaussian splatting shows promising results, outperforming preceding reconstruction methods while simultaneously reducing the overall computational requirements. The main success of 3D Gaussian splatting relies on the efficient use of a differentiable rasterizer to render the Gaussian scene representation.
View Article and Find Full Text PDFiScience
December 2024
Institute of Biotechnology, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland.
Advancements in noninvasive surface and internal imaging techniques, along with computational methods, have revolutionized 3D visualization of organismal morphology-enhancing research, medical anatomical analysis, and facilitating the preservation and digital archiving of scientific specimens. We introduce the SmARTR pipeline (Small Animal Realistic Three-dimensional Rendering), a comprehensive workflow integrating wet lab procedures, 3D data acquisition, and processing to produce photorealistic scientific data through 3D cinematic rendering. This versatile pipeline supports multiscale visualizations-from tissue-level to whole-organism details across diverse living organisms-and is adaptable to various imaging sources.
View Article and Find Full Text PDFCureus
November 2024
Faculty of Medicine, Institute for Implementation Science in Health Care, University of Zurich, Zurich, CHE.
Background: Generative artificial intelligence (AI) models that can produce photorealistic images from text descriptions have many applications in medicine, including medical education and the generation of synthetic data. However, it can be challenging to evaluate their heterogeneous outputs and to compare between different models. There is a need for a systematic approach enabling image and model comparisons.
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