Interactive Volumetric Region Growing for Brain Tumor Segmentation on MRI using WebGL
- Jonas Kordt – Hasso Plattner Institute
- Paul Brachmann – Hasso Plattner Institute
- Daniel Limberger – Hasso Plattner Institute
- Christoph Lippert – Hasso Plattner Institute
CATEGORY. Long Paper
KEYWORDS. Medical Imaging, MRI, Brain Tumor, Interactive Segmentation, Data Labeling, Region Growing, Progressive Rendering, WebGL
ABSTRACT. Volumetric segmentation of medical images is an essential tool in treatment planning and many longitudinal studies. While machine learning approaches promise to fully automate it, they most often still depend on manually labeled training data. We thus present a GPU-based volumetric region growing approach for semi-automatic brain tumor segmentation that can be interactively tuned. Additionally, we propose multidimensional transfer functions for ray tracing that allow users to judge the quality of the grown region. Our implementation produces a full brain tumor segmentation within a few milliseconds on consumer hardware. The visualization uses adaptive resolution scaling and progressive, asynchronous shading computation to maintain a stable 60 Hz refresh rate.