Illustrative Multi-volume Rendering for PET/CT Scans

In this paper we present illustrative visualization techniques for PET/CT datasets. PET/CT scanners acquire both PET and CT image data in order to combine functional metabolic information with structural anatomical information. Current visualization techniques mainly rely on 2D image fusion techniques to convey this combined information to physicians. We introduce an illustrative 3D visualization technique, specifically designed for use with PET/CT datasets. This allows the user to easily detect foci in the PET data and to localize these regions by providing anatomical contextual information from the CT data. Furthermore, we provide transfer function specifically designed for PET data that facilitates the investigation of interesting regions. Our technique allows users to get a quick overview of regions of interest and can be used in treatment planning, doctor-patient communication and interdisciplinary communication. We conducted a qualitative evaluation with medical experts to validate the utility of our method in clinical practice.

[1]  David W Townsend,et al.  PET/CT today and tomorrow. , 2004, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[2]  Georgios Sakas,et al.  Data Intermixing and Multi‐volume Rendering , 1999, Comput. Graph. Forum.

[3]  K J Zuiderveld,et al.  Integrated volume visualization of functional image data and anatomical surfaces using normal fusion , 2001, Human brain mapping.

[4]  Anna Puig,et al.  A framework for fusion methods and rendering techniques of multimodal volume data , 2004, Comput. Animat. Virtual Worlds.

[5]  Ivan Viola,et al.  Feature Emphasis and Contextual Cutaways for Multimodal Medical Visualization , 2007, EuroVis.

[6]  Joe Michael Kniss,et al.  Volume Rendering Multivariate Data to Visualize Meteorological Simulations: A Case Study , 2002, VisSym.

[7]  Werner M. Jainek,et al.  Illustrative Hybrid Visualization and Exploration of Anatomical and Functional Brain Data , 2008, Comput. Graph. Forum.

[8]  Markus Hadwiger,et al.  High-Quality Multimodal Volume Rendering for Preoperative Planning of Neurosurgical Interventions , 2007, IEEE Transactions on Visualization and Computer Graphics.

[9]  Klaus Mueller,et al.  Illustrative Focus+Context Approaches in Interactive Volume Visualization , 2010, Scientific Visualization: Advanced Concepts.

[10]  Heidrun Schumann,et al.  A Survey on Interactive Lenses in Visualization , 2014, EuroVis.

[11]  R. Leahy,et al.  Digimouse: a 3D whole body mouse atlas from CT and cryosection data , 2007, Physics in medicine and biology.

[12]  Jens Schneider,et al.  ClearView: An Interactive Context Preserving Hotspot Visualization Technique , 2006, IEEE Transactions on Visualization and Computer Graphics.

[13]  Kai Lawonn Illustrative visualization of medical data sets , 2014 .

[14]  Ross T. Whitaker,et al.  Curvature-based transfer functions for direct volume rendering: methods and applications , 2003, IEEE Visualization, 2003. VIS 2003..

[15]  Yeong-Gil Shin,et al.  Efficient Multimodality Volume Fusion Using Graphics Hardware , 2005, International Conference on Computational Science.

[16]  Stefan Bruckner,et al.  Information-based Transfer Functions for Multimodal Visualization , 2008, VCBM.

[17]  Thomas Ertl,et al.  GPU-based Multi-Volume Rendering for the Visualization of Functional Brain Images , 2006, SimVis.

[18]  David Dagan Feng,et al.  Visualizing Dual-Modality Rendered Volumes Using a Dual-Lookup Table Transfer Function , 2007, Computing in Science & Engineering.

[19]  H. Reeves,et al.  The Guild handbook of scientific illustration , 1991 .

[20]  Bart M. ter Haar Romeny,et al.  Flexible GPU-Based Multi-Volume Ray-Casting , 2008, VMV.

[21]  Kwan-Liu Ma,et al.  Interactive Multi-volume Visualization , 2002, International Conference on Computational Science.

[22]  Hong Qin,et al.  An Effective Illustrative Visualization Framework Based on Photic Extremum Lines (PELs) , 2007, IEEE Transactions on Visualization and Computer Graphics.

[23]  Ivan Viola,et al.  Importance-driven volume rendering , 2004, IEEE Visualization 2004.

[24]  D W. Townsend,et al.  Combined PET/CT Imaging in Oncology. Impact on Patient Management. , 2000, Clinical positron imaging : official journal of the Institute for Clinical P.E.T.

[25]  Adam Finkelstein,et al.  Suggestive contours for conveying shape , 2003, ACM Trans. Graph..

[26]  Frédo Durand,et al.  Apparent ridges for line drawing , 2007, ACM Trans. Graph..

[27]  Guang-Zhong Yang,et al.  pq-space Based Non-Photorealistic Rendering for Augmented Reality , 2007, MICCAI.

[28]  Mateu Sbert,et al.  Multimodal Data Fusion Based on Mutual Information , 2012, IEEE Transactions on Visualization and Computer Graphics.

[29]  Paul Kinahan,et al.  A combined PET/CT scanner for clinical oncology. , 2000, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[30]  Victoria Interrante,et al.  Enhancing transparent skin surfaces with ridge and valley lines , 1995, Proceedings Visualization '95.

[31]  Henrik Ohlsson,et al.  Concurrent Volume Visualization of Real-Time fMRI , 2010, VG@Eurographics.

[32]  Peter Winkler,et al.  Medical applications of multi-field volume rendering and VR techniques , 2004, VISSYM'04.

[33]  Tony DeRose,et al.  Toolglass and magic lenses: the see-through interface , 1993, SIGGRAPH.

[34]  Helwig Hauser,et al.  Visualization of Multi‐Variate Scientific Data , 2009, Comput. Graph. Forum.

[35]  David Dagan Feng,et al.  Visibility-driven PET-CT visualisation with region of interest (ROI) segmentation , 2013, The Visual Computer.