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Proceedings Paper

Intuitive parameter-free visualization of tumor vascularization using rotating connectivity projections
Author(s): Rafael Wiemker; Thomas Bülow; Roland Opfer; Sven Kabus; Ekta Dharaiya
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Paper Abstract

We present an effective and intuitive visualization of the macro-vasculature of a selected nodule or tumor in three-dimensional image data (e.g. CT, MR, US). For the differential diagnosis of nodules the possible distortion of adjacent vessels is one important clinical criterion. Surface renderings of vessel- and tumor-segmentations depend critically on the chosen parameter- and threshold-values for the underlying segmentation. Therefore we use rotating Maximum Intensity Projections (MIPs) of a volume of interests (VOI) around the selected tumor. The MIP does not require specific parameters, and allows much quicker visual inspection in comparison to slicewise navigation, while the rotation gives depth cues to the viewer. Of the vessel network within the VOI, however, not all vessels are connected to the selected tumor, and it is tedious to sort out which adjacent vessels are in fact connected and which are overlaid only by projection. Therefore we suggest a simple transformation of the original image values into connectivity values. In the derived connectedness-image each voxel value corresponds to the lowest image value encountered on the highest possible pathway from the tumor to the voxel. The advantage of the visualization is that no implicit binary decision is made whether a certain vessel is connected to the tumor or not, but rather the degree of connectedness is visualized as the brightness of the vessel. Non-connected structures disappear, feebly connected structures appear faint, and strongly connected structures remain in their original brightness. The visualization does not depend on delicate threshold values. Promising results have been achieved for pulmonary nodules in CT.

Paper Details

Date Published: 12 March 2008
PDF: 9 pages
Proc. SPIE 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images, 69161Z (12 March 2008); doi: 10.1117/12.765333
Show Author Affiliations
Rafael Wiemker, Philips Research Europe (Germany)
Thomas Bülow, Philips Research Europe (Germany)
Roland Opfer, Philips Research Europe (Germany)
Sven Kabus, Philips Research Europe (Germany)
Ekta Dharaiya, Philips Medical Systems (United States)


Published in SPIE Proceedings Vol. 6916:
Medical Imaging 2008: Physiology, Function, and Structure from Medical Images
Xiaoping P. Hu; Anne V. Clough, Editor(s)

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