A Streaming Volumetric Image Generation Framework for Development and Evaluation of Out-of-Core Methods

TL;DR

This paper introduces a fast, scalable framework for generating large volumetric images, including ground truth data, in a streaming manner, enabling efficient testing and evaluation of out-of-core image processing methods.

Contribution

The paper presents a novel nested sweeps algorithm for efficient volumetric data generation, capable of producing terabyte-scale images beyond main memory limits.

Findings

The framework can generate a 1TB volume in reasonable time.

Experimental analysis shows the algorithm outperforms alternative methods.

Implementation is integrated into existing visualization tools.

Abstract

Advances in 3D imaging technology in recent years have allowed for increasingly high resolution volumetric images of large specimen. The resulting datasets of hundreds of Gigabytes in size call for new scalable and memory efficient approaches in the field of image processing, where some progress has been made already. At the same time, quantitative evaluation of these new methods is difficult both in terms of the availability of specific data sizes and in the generation of associated ground truth data. In this paper we present an algorithmic framework that can be used to efficiently generate test (and ground truth) volume data, optionally even in a streaming fashion. As the proposed nested sweeps algorithm is fast, it can be used to generate test data on demand. We analyze the asymptotic run time of the presented algorithm and compare it experimentally to alternative approaches as well as a hypothetical best-case baseline method. In a case study, the framework is applied to the popular VascuSynth software for vascular image generation, making it capable of efficiently producing larger-than-main memory volumes which is demonstrated by generating a trillion voxel (1TB) image. Implementations of the presented framework are available online in the form of the modified version of Vascusynth and the code used for the experimental evaluation. In addition, the test data generation procedure has been integrated into the popular volume rendering and processing framework Voreen.