Stereoscopic display technologies, interaction paradigms, and rendering approaches for neurosurgical visualization

We conducted a comparative study of different stereoscopic display modalities (head-mounted display, polarized projection, and multiview lenticular display) to evaluate their efficacy in supporting manipulation and understanding of 3D content, specifically, in the context of neurosurgical visualization. Our study was intended to quantify the differences in resulting task performance between these choices of display technology. The experimental configuration involved a segmented brain vasculature and a simulated tumor. Subjects were asked to manipulate the vasculature and a pen-like virtual probe in order to define a vessel-free path from cortical surface to the targeted tumor. Because of the anatomical complexity, defining such a path can be a challenging task. To evaluate the system, we quantified performance differences under three different stereoscopic viewing conditions. Our results indicate that, on average, participants achieved best performance using polarized projection, and worst with the multiview lenticular display. These quantitative measurements were further reinforced by the subjects' responses to our post-test questionnaire regarding personal preferences.

[1]  A. James Stewart,et al.  Using Registration Uncertainty Visualization in a User Study of a Simple Surgical Task , 2006, MICCAI.

[2]  Stephen M Smith,et al.  Fast robust automated brain extraction , 2002, Human brain mapping.

[3]  David S. Ebert,et al.  VolQD: direct volume rendering of multi-million atom quantum dot simulations , 2005, VIS 05. IEEE Visualization, 2005..

[4]  Luis Serra,et al.  Volume-based tumor neurosurgery planning in the Virtual Workbench , 1998, Proceedings. IEEE 1998 Virtual Reality Annual International Symposium (Cat. No.98CB36180).

[5]  David H. Laidlaw,et al.  Interactive volume rendering of thin thread structures within multivalued scientific data sets , 2004, IEEE Transactions on Visualization and Computer Graphics.

[6]  Tovi Grossman,et al.  The design and evaluation of selection techniques for 3D volumetric displays , 2006, UIST.

[7]  Shumin Zhai,et al.  The “Silk Cursor”: investigating transparency for 3D target acquisition , 1994, CHI '94.

[8]  Colin Ware,et al.  Evaluating stereo and motion cues for visualizing information nets in three dimensions , 1996, TOGS.

[9]  Dennis Proffitt,et al.  Two-handed virtual manipulation , 1998, TCHI.

[10]  Hiroshi Ishii,et al.  Handsaw: tangible exploration of volumetric data by direct cut-plane projection , 2008, CHI.

[11]  A. Li,et al.  Comparison of two-dimensional vs three-dimensional camera systems in laparoscopic surgery , 1997, Surgical Endoscopy.

[12]  Tao Zhang,et al.  Direct Volume Rendering of Volumetric Protein Data , 2006, Computer Graphics International.

[13]  Tovi Grossman,et al.  An evaluation of depth perception on volumetric displays , 2006, AVI '06.

[14]  Benjamin D. Greenberg,et al.  An immersive virtual environment for DT-MRI volume visualization applications: a case study , 2001, Proceedings Visualization, 2001. VIS '01..

[15]  Ulrich Lang,et al.  Evaluation of a Collaborative Volume Rendering Application in a Distributed Virtual Environment , 2002, EGVE.

[16]  Kellogg S. Booth,et al.  Evaluating 3D task performance for fish tank virtual worlds , 1993, TOIS.

[17]  Marc Levoy,et al.  Display of surfaces from volume data , 1988, IEEE Computer Graphics and Applications.

[18]  Gregory D. Hager,et al.  Analysis of composite gestures with a coherent probabilistic graphical model , 2005, Virtual Real..