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Proceedings Paper

Automated 3D and 4D organ delineation for radiation therapy planning in the pelvic area
Author(s): Michael R. Kaus; Todd McNutt; Vladimir Pekar
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Paper Abstract

The determination of the treatment parameters in radiation therapy requires the segmentation of the patient anatomy. This procedure is usually performed by manual contouring of 2D slices, which may require several hours. The burden is considerably increased in the context of IMRT and 4D adaptive radiotherapy. Intensity Modulated Radiation Therapy (IMRT) offers the increased ability to accurately conform the radiation dose to the target. IMRT is typically applied in fractions over 30 days. 4D or adaptive radiotherapy aims at compensating the significant anatomical changes during the course of treatment based on additional imagery. The development of fast and robust automated segmentation tools is crucial for these novel treatment methods to succeed. The purpose of this paper is to automate organ contouring of 3D CT data and time series of 3D CT in radiation therapy planning (RTP). Automated organ delineation in CT is challenging due to poor soft tissue contrast and high inter- and intra-patient organ variability. This paper presents an automated model-based concept for organ delineation, based on adaptation of 3D deformable surface models to the boundaries of the anatomical structures of interest in 3D CT and time-series thereof. A feasibility study with 40 3D clinical datasets and a 3D time series with 19 datasets was done for the risk organs (bladder, rectum, and femoral heads) of the pelvic area. The results of the validation study show that the presented model-based approach is accurate (1-1.7 mm mean error) for the tested anatomical structures, and allows a significant reduction of time compared to manual organ contouring (minutes vs. hours).

Paper Details

Date Published: 12 May 2004
PDF: 11 pages
Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); doi: 10.1117/12.534822
Show Author Affiliations
Michael R. Kaus, Philips Research Labs. (Germany)
Todd McNutt, Philips Medical Systems (United States)
Vladimir Pekar, Philips Research Labs. (Germany)

Published in SPIE Proceedings Vol. 5370:
Medical Imaging 2004: Image Processing
J. Michael Fitzpatrick; Milan Sonka, Editor(s)

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