This project examines new three-dimensional ways of seeing objects in art history by adapting computational imaging and visualization techniques commonly associated with scientific and medical contexts. Building on traditions of close looking and material analysis, the project treats 3D models not simply as representations but as analytical instruments through which form, surface, and internal structure can be examined from multiple vantage points. Drawing conceptual parallels to medical imaging practices such as volumetric slicing, sectional views, and surface reconstruction, the project explores how these methods can be productively recontextualized for the study of cultural objects, where questions of materiality, facture, and spatial organization are central to interpretation.
The project is grounded in open-source 3D software and Python-based visualization libraries, including PyVista, which enable direct, programmable engagement with OBJ files and mesh geometry. These tools support a range of analytical visualizations, from cross-sectional and wireframe views to surface curvature and structural mapping, allowing scholars and students to interrogate objects in ways that exceed the limitations of photography or static display. By integrating techniques drawn from scientific visualization into art historical inquiry, the project advances an expanded visual epistemology for material culture studies, demonstrating how open, computational 3D methods can support rigorous, reproducible, and critically informed approaches to seeing, analyzing, and teaching objects in the humanities.