Abstract
With the increasing availability of high-resolution isotropic three- or four-dimensional medical datasets from sources such as magnetic resonance imaging, computed tomography, and ultrasound, volumetric image visualization techniques have increased in importance. Over the past two decades, a number of new algorithms and improvements have been developed for practical clinical image display. More recently, further efficiencies have been attained by designing and implementing volume-rendering algorithms on graphics processing units (GPUs). In this paper, we review volumetric image visualization pipelines, algorithms, and medical applications. We also illustrate our algorithm implementation and evaluation results, and address the advantages and drawbacks of each algorithm in terms of image quality and efficiency. Within the outlined literature review, we have integrated our research results relating to new visualization, classification, enhancement, and multimodal data dynamic rendering. Finally, we illustrate issues related to modern GPU working pipelines, and their applications in volume visualization domain.
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References
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Acknowledgments
The authors would like to thank J. Moore, C. Wedlake, and Dr. U. Aladl for technical support and assistance; K. Wang and Dr. M. Wachowiak for valuable discussions and assistance; and Ms. J. Williams for editorial assistance. They would also like to thank the anonymous editors and reviewers. This project was supported by the Canadian Institutes for Health Research (Grant MOP 74626), the National Science and Engineering Research Council of Canada (Grant R314GA01), the Ontario Research and Development Challenge Fund, the Canadian Foundation for Innovation and the Ontario Innovation Trust, as well as the Graduate Scholarships from the Ontario Ministry of Education and the University of Western Ontario.
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Zhang, Q., Eagleson, R. & Peters, T.M. Volume Visualization: A Technical Overview with a Focus on Medical Applications. J Digit Imaging 24, 640–664 (2011). https://doi.org/10.1007/s10278-010-9321-6
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DOI: https://doi.org/10.1007/s10278-010-9321-6