The Distance-based Focus+Context Models for Exploration of Large Volumetric Medical Datasets (IEEE)
The visualization and exploration of large volumetric medical datasets from high resolution CT and MRI medical images are slow in rendering speed due the amount data to be processed. We present distance-based methods to address the issues based on GPU volume ray-casting and the idea of focus and context, providing a simultaneous visualization of different rendering styles for the focus region defined by a superquadric or a plane and its context. Experiments on large volumetric medical datasets show that our methods are efficient enough for interactive visualization and effective in directly guiding the user to region of interest (ROI).
Paper available at IEEE.