@article{HardcastleTomeCannonetal.2012,
  author    = {Hardcastle, Nicholas and Tom{\´e}, Wolfgang A. and Cannon, Donald M. and Brouwer, Charlotte L. and Wittendorp, Paul W. H. and Dogan, Nesrin and Guckenberger, Matthias and Allaire, St{\´e}phane and Mallya, Yogish and Kumar, Prashant and Oechsner, Markus and Richter, Anne and Song, Shiyu and Myers, Michael and Polat, B{\"u}lent and Bzdusek, Karl},
  title     = {A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy},
  series = {Radiation Oncology},
  volume    = {7},
  journal   = {Radiation Oncology},
  number    = {90},
  doi       = {10.1186/1748-717X-7-90},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-134756},
  year      = {2012},
  abstract  = {Background: Adaptive Radiotherapy aims to identify anatomical deviations during a radiotherapy course and modify the treatment plan to maintain treatment objectives. This requires regions of interest (ROIs) to be defined using the most recent imaging data. This study investigates the clinical utility of using deformable image registration (DIR) to automatically propagate ROIs. Methods: Target (GTV) and organ-at-risk (OAR) ROIs were non-rigidly propagated from a planning CT scan to a per-treatment CT scan for 22 patients. Propagated ROIs were quantitatively compared with expert physician-drawn ROIs on the per-treatment scan using Dice scores and mean slicewise Hausdorff distances, and center of mass distances for GTVs. The propagated ROIs were qualitatively examined by experts and scored based on their clinical utility. Results: Good agreement between the DIR-propagated ROIs and expert-drawn ROIs was observed based on the metrics used. 94\% of all ROIs generated using DIR were scored as being clinically useful, requiring minimal or no edits. However, 27\% (12/44) of the GTVs required major edits. Conclusion: DIR was successfully used on 22 patients to propagate target and OAR structures for ART with good anatomical agreement for OARs. It is recommended that propagated target structures be thoroughly reviewed by the treating physician.},
  language  = {en}
}
@phdthesis{Oechsner2011,
  author    = {Oechsner, Markus},
  title     = {Morphologische und funktionelle <sup>1</sup>H-Magnetresonanztomographie der menschlichen Lunge bei 0.2 und 1.5 Tesla},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-66942},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2011},
  abstract  = {Das Ziel dieser Arbeit war es, Methoden und Techniken f{\"u}r die morphologische und funktionelle Bildgebung der menschlichen Lunge mittels Kernspintomographie bei Feldst{\"a}rken von 0,2 Tesla und 1,5 Tesla zu entwickeln und zu optimieren. Bei 0,2 Tesla wurde mittels der gemessenen Relaxationszeiten T1 und T2* eine 2D und eine 3D FLASH Sequenz zur Untersuchung der Lungenmorphologie optimiert. Sauerstoffgest{\"u}tzte Messungen der Relaxationszeiten T1 und T2* sowie eine SpinLabeling Sequenz liefern funktionelle Informationen {\"u}ber den Sauerstofftransfer und die Perfusion der Lungen. Bei 1,5 Tesla wurde die Lungenperfusion mittels MR-Kontrastmittel mit einer 2D und einer 3D Sequenz unter Verwendung der Pr{\"a}bolus Technik quantifiziert. Zudem wurden zwei MR-Navigationstechniken entwickelt, die es erm{\"o}glichen Lungenuntersuchungen unter freier Atmung durchzuf{\"u}hren und aus den Daten artefaktfreie Bilder zu rekonstruieren. Diese Techniken k{\"o}nnen in verschiedenste Sequenzen f{\"u}r die Lungenbildgebung implementiert werden, ohne dass die Messzeit dadurch signifikant verl{\"a}ngert wird.},
  subject      = {NMR-Bildgebung},
  language  = {de}
}