Hybrid rendering of exploded views for medical image atlas visualization

Medical image atlases contain much information about human anatomy, but learning the shapes of anatomical regions and making sense of the overall structure defined in the atlas can be problematic. Atlases may contain hundreds of regions with complex shapes which can be tightly packed together. This makes visualisation difficult since the shapes can fit together in complex ways and visually obscure each other. In this work, we describe a technique which enables interactive exploration of medical image atlases that permits the hierarchical structure of the atlas and the content of an underlying medical image to be investigated simultaneously. Our method enables a user to create visualizations of the atlas similar to the exploded views used in technical illustrations to show the structure of mechanical assemblies. These views are constrained by the geometry of the atlas and the hierarchical structure to reduce the complexity of user interaction. We also enable the user to explode the atlas meshes themselves. The atlas meshes are registered with a medical image which is displayed on the cut surfaces of the meshes using raycasting. Results from the AAL human brain atlas are presented and discussed

Improving Object Composition Visualization via Exploded Views

Manipulating internal parts of a 3D model can be a time consuming and tedious task. On one hand, letting a user to define the position of each part can depend on the type of the object and the expertise of using modeling tools. On the other hand, using transparent visualization or cut techniques can mislead the spatial relation position between different parts of a model. An approach that attempts to mitigate previous issues is an exploded view. In this work, we introduce an improvement to the current state of exploded views by adding two features: an algorithm to automatically position the camera to show an optimal exploded view for a selected target on a variety of models, and a qualitative user study to obtain features\u27 feedback of our algorithm used by 3D software users. Our work is based on two key elements: a low-level data structure using bounding boxes (BB) and an optimization that minimizes an energy function dependent on two search spaces in parallel. Using BBs allows us to generalize the type of exploded views to any geometrical model while maintaining interactive frame-rates in our application. Simulated annealing, along with two heuristics, is used to solve the optimization. For a selected part, the optimization heuristics help to guide the direction of explosion and to move the part\u27s neighborhood in a recursive manner if necessary. We decide to call the neighbor\u27s movement megamove. Our technique is applied to a variety of models, such as furniture, anatomical datasets, and vehicles. We also test our application with users with knowledge of 3D software using a questionnaire. The user study aids our analysis of the likelihood for our exploded views to be an improvement for 3D software user expectations