Immersive 3D Manifolds from Deep Embeddings: Evaluation of Image Classifications in VR - Boykin, Meaghan; Santos, Guilherme Melo dos; Godoy, Carlos Gurjão de; Coelho, Regina C.; Ushizima, Daniela (Anais do Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS); 2026: Anais do XXVI Simpósio Brasileiro de Computação Aplicada à SaúdeDO - 10.5753/sbcas.2026.21302, 2026)
We show that our Meta Quest 3/3S application provides an immersive environment for the exploration of 3D manifolds generated from deep learning embeddings. Built with Unreal Engine 5.5.4, our tool enables the evaluation and sorting of biomedical specimens classifications by projecting high-dimensional semantic features into a navigable 3D space. Within the virtual environment, users can validate automated results by interactively categorizing images into defined spatial clusters, with the ability to export refined datasets via CSV. This systematic workflow improves quality control for large-scale imaging, offering researchers an intuitive interface to rapidly sort complex biological datasets.