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Dr.-Ing. Christian Schaller

Alumnus of the Pattern Recognition Lab of the Friedrich-Alexander-Universität Erlangen-Nürnberg

Implementing Corporate Creativity and Innovations


Precise localization of moving targets in the thorax and abdomen during the course of treatment can be used to increase local control via dose escalation while reducing the severity of normal tissue complication. Localization of targets in real time with radio-opaque marker is not practical considering the excess radiation dose to the patient and potential complications of implantation. Various external surrogates can be used to give indications of locations of the targets during the breathing process. However, there is a great deal of uncertainty in correlation between external surrogates and internal target positions/trajectory during respiratory cycles. This is due to the fact that the correlation tends to vary through time as the patient's breathing pattern changes. In this project, the problem of establishing the correlation between a surrogate signal and an internal target prior to treatment is adressed. We have developed an algorithm that automatically establishes correspondences between the fluoroscopic sequence frames taken from the patient on the day of treatment and the various phases of a 4DCT planning data set. Image based mapping/synchronization procedure is performed using an underlying Markov model established for the breathing process. The mapping procedure is formulated as an optimization process and is solved efficiently using a dynamic programming technique. Results on the phantom, synthetic, and real patient data demonstrate the effectiveness of the proposed method in coping with respiratory correlation variations. The approach could primarily be used for automatic gating interval adaptation in the gated radiotherapy.


In cooperation with Siemens Corporate Research, Princeton, NJ, USA an image based mapping/synchronization procedure was developed. It automatically
labels pre-treatment fluoroscopic image frames with the corresponding
phase from a 4DCT. The mapping procedure is formulated as an optimization
process, which finds an optimal mapping maximizing the image similarity between the corresponding pairs, while preserving a temporal coherency to an established Markov model for breathing. The mapping procedure also detects the frames with no corresponding phase from the planning 4DCT. The fluoroscopic image based verification addresses the problem of establishing the correlation between surrogate signal and internal target prior to treatment. By virtue of having the labels generated from a mapping process, we can adaptively change the surrogate gating interval to the up-to-date breathing pattern of the patient. Results on phantom, synthetic, and patient data shows in average 93 percent of frames are correctly labeled.

depicts the coronal slices of planning 4DCT data sets with visible contour lines.
demonstrates two frames of a fluoroscopic acquisition overlaid with the outlines of the projected structures from the planning 4D dataset
Both pictures depict a 4DCT frame with matching fluoroscopic frame with overlaid contours for phantom and patient datasets, respectively.
The bottom row shows the corresponding image similarity matrix for each case.


Schaller, Christian; Khamene, Ali; Hornegger, Joachim
Image Based Time Series Synchronization for Periodically Moving Targets
3rd Russian-Bavarian Conference on Biomedical Engineering
(3rd Russian-Bavarian Conference on Biomedical Engineering Erlangen 2.-3.07.2007)
Vol. 1 Erlangen : Union aktuell 2007, pp. 106-110 - ISBN 3-921713-33-X

Khamene, Ali; Schaller, Christian; Hornegger, Joachim; Celi, Juan Carlos; Ofstad, Barbara;
Rietzel, Eike; Li, X. Allen; Tai, An; Bayouth, John
A Novel Image Based Verification Method for Respiratory Motion Management in Radiation Therapy
In: Dimitris Metaxas; Baba C. Vemuri; Amnon Shashua; Harry Shum (Eds.)
Eleventh IEEE International Conference on Computer Vision
(ICCV'07 Rio de Janeiro, Brasilien 14.10.2007 - 20.10.2007)
DVD Proceedings : Omnipress 2007, pp. n/a - ISBN 978-1-4244-1631-8

Khamene, Ali (Princeton, NJ, US), Florin, Charles Henri (Exton, PA, US), Celi, Juan Carlos (Bensheim, DE),
Ofstad, Barbara (Weinheim, DE), Rousson, Mikael (Trenton, NJ, US), Sauer, Frank (Princeton, NJ, US),
Schaller, Christian (Teublitz, DE)    2008    
United States    Siemens Corporate Research, Inc. (Princeton, NJ, US)    20080031404

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