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Proceedings Paper

Multimodal 3D PET/CT system for bronchoscopic procedure planning
Author(s): Ronnarit Cheirsilp; William E. Higgins
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Paper Abstract

Integrated positron emission tomography (PET) / computed-tomography (CT) scanners give 3D multimodal data sets of the chest. Such data sets offer the potential for more complete and specific identification of suspect lesions and lymph nodes for lung-cancer assessment. This in turn enables better planning of staging bronchoscopies. The richness of the data, however, makes the visualization and planning process difficult. We present an integrated multimodal 3D PET/CT system that enables efficient region identification and bronchoscopic procedure planning. The system first invokes a series of automated 3D image-processing methods that construct a 3D chest model. Next, the user interacts with a set of interactive multimodal graphical tools that facilitate procedure planning for specific regions of interest (ROIs): 1) an interactive region candidate list that enables efficient ROI viewing in all tools; 2) a virtual PET-CT bronchoscopy rendering with SUV quantitative visualization to give a “fly through" endoluminal view of prospective ROIs; 3) transverse, sagittal, coronal multi-planar reformatted (MPR) views of the raw CT, PET, and fused CT-PET data; and 4) interactive multimodal volume/surface rendering to give a 3D perspective of the anatomy and candidate ROIs. In addition the ROI selection process is driven by a semi-automatic multimodal method for region identification. In this way, the system provides both global and local information to facilitate more specific ROI identification and procedure planning. We present results to illustrate the system's function and performance.

Paper Details

Date Published: 28 February 2013
PDF: 14 pages
Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86702X (28 February 2013); doi: 10.1117/12.2004571
Show Author Affiliations
Ronnarit Cheirsilp, Pennsylvania State Univ. (United States)
William E. Higgins, Pennsylvania State Univ. (United States)

Published in SPIE Proceedings Vol. 8670:
Medical Imaging 2013: Computer-Aided Diagnosis
Carol L. Novak; Stephen Aylward, Editor(s)

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