AnatomyCarve: A VR occlusion management technique for medical images based on segment-aware clipping

TL;DR

AnatomyCarve is a VR-based occlusion management technique that creates high-quality, interactive medical illustrations by segment-aware clipping, improving visualization and understanding of 3D medical images for education and clinical use.

Contribution

The paper introduces AnatomyCarve, a novel VR technique for segment-aware clipping that produces illustrative visualizations similar to anatomy books, enhancing 3D medical image comprehension.

Findings

High user satisfaction in usability study

Effective in surgical planning with neurosurgeons

Enables customized anatomical visualizations

Abstract

Visualizing 3D medical images is challenging due to self-occlusion, where anatomical structures of interest can be obscured by surrounding tissues. Existing methods, such as slicing and interactive clipping, are limited in their ability to fully represent internal anatomy in context. In contrast, hand-drawn medical illustrations in anatomy books manage occlusion effectively by selectively removing portions based on tissue type, revealing 3D structures while preserving context. This paper introduces AnatomyCarve, a novel technique developed for a VR environment that creates high-quality illustrations similar to those in anatomy books, while remaining fast and interactive. AnatomyCarve allows users to clip selected segments from 3D medical volumes, preserving spatial relations and contextual information. This approach enhances visualization by combining advanced rendering techniques with natural user interactions in VR. Usability of AnatomyCarve was assessed through a study with non-experts, while surgical planning effectiveness was evaluated with practicing neurosurgeons and residents. The results show that AnatomyCarve enables customized anatomical visualizations, with high user satisfaction, suggesting its potential for educational and clinical applications.