A direct volume rendering visualization approach for serial PET–CT scans that preserves anatomical consistency
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Our aim was to develop an interactive 3D direct volume rendering (DVR) visualization solution to interpret and analyze complex, serial multi-modality imaging datasets from positron emission tomography–computed tomography (PET–CT).
Our approach uses: (i) a serial transfer function (TF) optimization to automatically depict particular regions of interest (ROIs) over serial datasets with consistent anatomical structures; (ii) integration of a serial segmentation algorithm to interactively identify and track ROIs on PET; and (iii) parallel graphics processing unit (GPU) implementation for interactive visualization.
Our DVR visualization more easily identifies changes in ROIs in serial scans in an automated fashion and parallel GPU computation which enables interactive visualization.
Our approach provides a rapid 3D visualization of relevant ROIs over multiple scans, and we suggest that it can be used as an adjunct to conventional 2D viewing software from scanner vendors.
KeywordsDirect volume rendering PET–CT visualization Transfer function Serial segmentation
This study was funded in part by the Australia Research Council (DP160103675).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
For this type of study, formal consent is not required. The testing data were collected at our institution with approval from the institutional review board.
Informed consent was obtained from all individual participants included in the study.
- 1.Pfister H, Lorensen B, Bajaj C, Kindlmann G, Schroeder W, Avila L, Martin K, Machiraju R (2007) The transfer function bake-off. IEEE Comput Graph Appl 21(3):16–22Google Scholar
- 6.Tzeng F, Ma K (2005) Intelligent feature extraction and tracking for visualizing large-scale 4D flow simulations. In: Proceedings of ACM/IEEE supercomputing 05Google Scholar
- 7.Akiba H, Fout N, Ma K (2006) Simultaneous classification of time-vying volume data based on the time histogram. In: Proceedings of EuroVis 06Google Scholar
- 9.Kim J, Hu Y, Eberl S, Feng D, Fulham M (2008) A fully automatic bed/linen segmentation for fused PET/CT MIP rendering. In: Proceedings of EMBC 08Google Scholar
- 11.Bi L, Kim J, Wen L, Kumar A, Fulham M, Feng D (2013) Cellular automata and anisotropic diffusion filter based interactive tumor segmentation for positron emission tomography. In: Proceedings of EMBC 13Google Scholar
- 17.Kniss J, Kindlmann G, Hansen C (2001) Interactive volume rendering using multi-dimensional transfer functions and direct manipulation widgets. In: Proceedings of IEEE Vis 01Google Scholar