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DTSTAMP:20260817T171530Z
LOCATION:Hall C\, C Block\, Level 4
DTSTART;TZID=Asia/Tokyo:20241206T160000
DTEND;TZID=Asia/Tokyo:20241206T180000
UID:siggraphasia_SIGGRAPH Asia 2024_sess208_real_106@linklings.com
SUMMARY:Viewtify: Next-Generation Medical Image Viewer with Stereoscopic D
 isplay
DESCRIPTION:Hirofumi Seo (SCIEMENT, Inc.)\n\nViewtify® fully leverages a g
 ame engine and GPU to generate and render high-quality 3DCG from CT and MR
 I images in real time. By using stereoscopic displays, it presents 3D visu
 als with depth information. Its high-speed processing also enables the rea
 l-time display of 4D CT and 4D MRI images as animated 3DCG.\n\n1 Introduct
 ion\n\n3DCG reconstruction from volumetric medical data, such as CT or MRI
  images, is commonly used in medical practice. There are many medical imag
 ing software for it, from free tools like OsiriX (Pixmeo SARL, Switzerland
 ) and 3D Slicer (open source) to commercial products like 3mensio (3mensio
  Medical Imaging B.V., Netherlands) and Mimics (Materialise NV, Belgium). 
 However, the 3D rendering techniques are often simple and outdated, making
  the visuals less clear. Recently, some software like syngo.via (Siemens H
 ealthineers, Germany) has applied global illumination for volume rendering
 , but resolution drops during manipulation. Unclear shading and resolution
  drop during interaction make interactive operations and understanding com
 plex structures difficult.\nViewtify® (SCIEMENT, Inc., Japan) enables real
 -time 3DCG adjustments by achieving both fast 3D surface mesh synthesis fr
 om CT or MRI images via thresholding and high-quality real-time rendering.
  It also supports commercial glasses-free, eye-sensing stereoscopic displa
 ys (ELF-SR1, ELF-SR2 (SONY, Japan), and SpatialLabs View Pro (Acer Inc., T
 aiwan)), presenting the 3D visuals as objects with depth information.\n\n2
  Technical Overview\n\nViewtify is developed on Unreal Engine (Epic Games,
  Inc., U.S.) for high-quality real-time rendering, while the 3D mesh is ge
 nerated on the GPU using custom development with CUDA. By sharing GPU reso
 urces between them, 3D data synthesized by CUDA can be directly read by Un
 real Engine. For example, a mesh with about 9.6 million triangles has been
  produced from 512×512x412 (about 100 million) voxels. With an NVIDIA GeFo
 rce RTX 3090, this takes about 20 milliseconds, allowing for the rendering
  and display of 4D CT images at up to 40 fps in 4K resolution, including u
 ser interface elements.\n\n3 High-Quality Rendering\n\nViewtify leverages 
 Unreal Engine for modern, high-quality rendering, which significantly enha
 nces the understanding of surgical anatomy by emphasizing shading. While a
  stereoscopic display can help with depth perception, exaggerated shading 
 provides a clearer view, making modern rendering techniques essential for 
 understanding complex anatomy.\n\n4 Clinical Applications\n\nViewtify is n
 ot yet a medical device, but it has facilitated biventricular repair inste
 ad of univentricular repair in congenital heart disease by providing a 3D 
 understanding of intracardiac structures. It has also aided in estimating 
 endoleak types by visually analyzing their location and shape after abdomi
 nal stent-graft placement. Case reports and retrospective studies utilizin
 g Viewtify are emerging, particularly in cardiac surgery.\n\n5 Conclusion\
 n\nViewtify employs the simplest and most classic method of thresholding b
 ut can effectively generates high-quality 3DCG in real time.\nBy supportin
 g stereoscopy, it also faithfully presents the information in CT and MRI i
 mages. There still remains significant potential for 3DCG to contribute to
  the medical field.\n\nRegistration Category: Enhanced Access, Full Access
 , Full Access Supporter\n\nLanguage Format: English Language\n\nSession Ch
 air: Takahito Tejima (Polyphony Digital Inc.)\n\n
URL:https://asia.siggraph.org/2024/program/?id=real_106&sess=sess208
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