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Instant Feedback Rapid Prototyping for GPU-Accelerated Computation, Manipulation, and Visualization of
Maximilian Malek1, Christoph W Sensen1
1Institute of Computational Biotechnology, Graz University of Technology, Graz, Austria.
Objective:
We have created an open-source application and framework for rapid GPU-accelerated prototyping, targeting image analysis, including volumetric images such as CT or MRI data.
Methods:
A visual graph editor enables the design of processing pipelines without programming. Run-time compiled compute shaders enable prototyping of complex operations in a matter of minutes.
Results:
GPU-acceleration increases processing the speed by at least an order of magnitude when compared to traditional multithreaded CPU-based implementations, while offering the flexibility of scripted implementations.
Conclusion:
Our framework enables real-time, intuition-guided accelerated algorithm and method development, supported by built-in scriptable visualization.
Significance:
This is, to our knowledge, the first tool for medical data analysis that provides both high performance and rapid prototyping. As such, it has the potential to act as a force multiplier for further research, enabling handling of high-resolution datasets while providing quasi-instant feedback and visualization of results.
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