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Proceedings Paper

Hierarchical parsing and semantic navigation of full body CT data
Author(s): Sascha Seifert; Adrian Barbu; S. Kevin Zhou; David Liu; Johannes Feulner; Martin Huber; Michael Suehling; Alexander Cavallaro; Dorin Comaniciu
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Paper Abstract

Whole body CT scanning is a common diagnosis technique for discovering early signs of metastasis or for differential diagnosis. Automatic parsing and segmentation of multiple organs and semantic navigation inside the body can help the clinician in efficiently obtaining accurate diagnosis. However, dealing with the large amount of data of a full body scan is challenging and techniques are needed for the fast detection and segmentation of organs, e.g., heart, liver, kidneys, bladder, prostate, and spleen, and body landmarks, e.g., bronchial bifurcation, coccyx tip, sternum, lung tips. Solving the problem becomes even more challenging if partial body scans are used, where not all organs are present. We propose a new approach to this problem, in which a network of 1D and 3D landmarks is trained to quickly parse the 3D CT data and estimate which organs and landmarks are present as well as their most probable locations and boundaries. Using this approach, the segmentation of seven organs and detection of 19 body landmarks can be obtained in about 20 seconds with state-of-the-art accuracy and has been validated on 80 CT full or partial body scans.

Paper Details

Date Published: 27 March 2009
PDF: 8 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 725902 (27 March 2009); doi: 10.1117/12.812214
Show Author Affiliations
Sascha Seifert, Siemens Corporate Technology (Germany)
Adrian Barbu, Florida State Univ. (United States)
S. Kevin Zhou, Siemens Corporate Research (United States)
David Liu, Siemens Corporate Research (United States)
Johannes Feulner, Siemens Corporate Technology (Germany)
Martin Huber, Siemens Corporate Technology (Germany)
Michael Suehling, Siemens Corporate Technology (Germany)
Alexander Cavallaro, Univ. Hospital Erlangen (Germany)
Dorin Comaniciu, Siemens Corporate Research (United States)

Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)

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