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Proceedings Paper

Advanced 3D image processing techniques for liver and hepatic tumor location and volumetry
Author(s): Stephane Chemouny; Henri Joyeux; Bruno Masson; Frederic Borne; Marc Jaeger; Olivier Monga
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Paper Abstract

To assist radiologists and physicians in diagnosing, and in treatment planning and evaluating in liver oncology, we have developed a fast and accurate segmentation of the liver and its lesions within CT-scan exams. The first step of our method is to reduce spatial resolution of CT images. This will have two effects: obtain near isotropic 3D data space and drastically decrease computational time for further processing. On a second step a 3D non-linear `edge- preserving' smoothing filtering is performed throughout the entire exam. On a third step the 3D regions coming out from the second step are homogeneous enough to allow a quite simple segmentation process, based on morphological operations, under supervisor control, ending up with accurate 3D regions of interest (ROI) of the liver and all the hepatic tumors. On a fourth step the ROIs are eventually set back into the original images, features like volume and location are immediately computed and displayed. The segmentation we get is as precise as a manual one but is much faster.

Paper Details

Date Published: 21 May 1999
PDF: 11 pages
Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); doi: 10.1117/12.348633
Show Author Affiliations
Stephane Chemouny, CIRAD-MEB (France)
Henri Joyeux, Institut du Cancer de Montpellier (France)
Bruno Masson, Institut du Cancer de Montpellier (France)
Frederic Borne, CIRAD-MEB (France)
Marc Jaeger, Ecole Nationale Superieure des Mines (France)
Olivier Monga, INRIA (France)


Published in SPIE Proceedings Vol. 3661:
Medical Imaging 1999: Image Processing
Kenneth M. Hanson, Editor(s)

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