A computational medical XR discipline

TL;DR

Computational Medical XR (CMXR) integrates computational science, neuroscience, and extended reality to address complex medical and neuroscience challenges through innovative AI and spatial computing solutions.

Contribution

This paper introduces CMXR as a new interdisciplinary framework combining computational methods with XR for medical applications, advancing beyond previous clinical XR approaches.

Findings

Proposes a unified framework for medical XR applications.

Integrates neural simulation, computational geometry, and deep learning.

Addresses diverse medical tasks from training to therapy.

Abstract

Computational Medical Extended Reality (CMXR), brings together life sciences and neuroscience with mathematics, engineering and computer science. It unifies computational science (scientific computing) with intelligent extended reality and spatial computing for the medical field. It significantly differs from previous "Clinical XR" or "Medical XR" terms, as it is focusing on how to integrate computational methods from neural simulation to computational geometry, computational vision and computer graphics with deep learning models to solve specific hard problems in medicine and neuroscience: from low/no-code/genAI authoring platforms to deep learning XR systems for training, planning, operative navigation, therapy and rehabilitation.