Ascribe New Dimensions to Scientific Data Visualization with VR
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866912333866991616 |
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| author | Ushizima, Daniela Santos, Guilherme Melo dos Sordo, Zineb Pandolfi, Ronald Donatelli, Jeffrey |
| author_facet | Ushizima, Daniela Santos, Guilherme Melo dos Sordo, Zineb Pandolfi, Ronald Donatelli, Jeffrey |
| contents | For over half a century, the computer mouse has been the primary tool for interacting with digital data, yet it remains a limiting factor in exploring complex, multi-scale scientific images. Traditional 2D visualization methods hinder intuitive analysis of inherently 3D structures. Virtual Reality (VR) offers a transformative alternative, providing immersive, interactive environments that enhance data comprehension. This article introduces ASCRIBE-VR, a VR platform of Autonomous Solutions for Computational Research with Immersive Browsing \& Exploration, which integrates AI-driven algorithms with scientific images. ASCRIBE-VR enables multimodal analysis, structural assessments, and immersive visualization, supporting scientific visualization of advanced datasets such as X-ray CT, Magnetic Resonance, and synthetic 3D imaging. Our VR tools, compatible with Meta Quest, can consume the output of our AI-based segmentation and iterative feedback processes to enable seamless exploration of large-scale 3D images. By merging AI-generated results with VR visualization, ASCRIBE-VR enhances scientific discovery, bridging the gap between computational analysis and human intuition in materials research, connecting human-in-the-loop with digital twins. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_13448 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Ascribe New Dimensions to Scientific Data Visualization with VR Ushizima, Daniela Santos, Guilherme Melo dos Sordo, Zineb Pandolfi, Ronald Donatelli, Jeffrey Graphics Artificial Intelligence Computational Engineering, Finance, and Science For over half a century, the computer mouse has been the primary tool for interacting with digital data, yet it remains a limiting factor in exploring complex, multi-scale scientific images. Traditional 2D visualization methods hinder intuitive analysis of inherently 3D structures. Virtual Reality (VR) offers a transformative alternative, providing immersive, interactive environments that enhance data comprehension. This article introduces ASCRIBE-VR, a VR platform of Autonomous Solutions for Computational Research with Immersive Browsing \& Exploration, which integrates AI-driven algorithms with scientific images. ASCRIBE-VR enables multimodal analysis, structural assessments, and immersive visualization, supporting scientific visualization of advanced datasets such as X-ray CT, Magnetic Resonance, and synthetic 3D imaging. Our VR tools, compatible with Meta Quest, can consume the output of our AI-based segmentation and iterative feedback processes to enable seamless exploration of large-scale 3D images. By merging AI-generated results with VR visualization, ASCRIBE-VR enhances scientific discovery, bridging the gap between computational analysis and human intuition in materials research, connecting human-in-the-loop with digital twins. |
| title | Ascribe New Dimensions to Scientific Data Visualization with VR |
| topic | Graphics Artificial Intelligence Computational Engineering, Finance, and Science |
| url | https://arxiv.org/abs/2504.13448 |