Otto Sauer

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The principles and practice of stereotac-tic body radiotherapy (SBRT) were transferred from cranial stereotactic radiother-apy/radiosurgery in the mid-1990s by pioneering work at the Karolinska Hospital in Sweden [1]. This concept was quickly adopted and further developed in Ja-pan [2] and Germany [3, 4]. At the beginning , SBRT was predominantly defined by(More)
A method is described which provides fully automatic detection of corresponding anatomical landmarks in volume scans taken at different respiratory states. The resulting control points are needed for creating a volumetric deformation model for motion compensation in radiotherapy. Prior to treatment two CT volumes are taken, one scan during inhalation, one(More)
BACKGROUND To introduce a novel method of patient positioning for high precision intracranial radiotherapy. METHODS An infrared(IR)-array, reproducibly attached to the patient via a vacuum-mouthpiece(vMP) and connected to the table via a 6 degree-of-freedom(DoF) mechanical arm serves as positioning and fixation system. After IR-based manual prepositioning(More)
BACKGROUND Evaluation of set up error detection by a transperineal ultrasound in comparison with a cone beam CT (CBCT) based system in external beam radiation therapy (EBRT) of prostate cancer. METHODS Setup verification was performed with transperineal ultrasound (TPUS) and CBCT for 10 patients treated with EBRT for prostate cancer. In total, 150(More)
For an effective radiotherapy treatment with external beams it is essential to know the tumour's position. To accurately localise a tumour interfractional and intrafractional organ movement have to be taken into account. With a global rigid registration of the planning and the treatment CT data, the target volume and the actual isocentre may be found in the(More)
We present a fast, interactive local rigid registration application to localize tumour's position for radiotherapy. The aim of the application is to automatically localize in a therapy CT dataset the target volume marked in a plan CT before applying a therapy. The algorithm is fast because it restricts the registration to a small area of the whole dataset.(More)
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