Patrik Raudaschl

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The favored treatment for many hip fractures is a sliding hip screw, and its usage is expected to increase in the future. Failures can be reduced, and complications detected earlier by semi-automated CT image analysis. The most frequent failure is due to the screw cut-out from the femoral head. An image-based method was developed for early detection of(More)
We investigate efficient algorithmic realisations for robust deconvolution of grey-value images with known space-invariant point-spread function, with emphasis on 1D motion blur scenarios. The goal is to make deconvolution suitable as preprocessing step in automated image processing environments with tight time constraints. Candidate deconvolution methods(More)
PURPOSE Multiatlas based segmentation is largely used in many clinical and research applications. Due to its good performances, it has recently been included in some commercial platforms for radiotherapy planning and surgery guidance. Anyway, to date, a software with no restrictions about the anatomical district and image modality is still missing. In this(More)
PURPOSE In this work we present the validation of Plastimatch MABS, an open source software for multi atlas based segmentation of medical images. METHODS The validation was performed on two different clinical datasets: 1) 25 CT image volumes of patients treated for H&N cancer; 2) 20 MRI series of patients having a neurological diagnosis. For the first(More)
Atlas-based segmentation is a frequently used approach in medical imaging and multi atlas-based segmentation (MABS) has achieved great success for various applications. In order to simultaneously exploit the capabilities of MABS, limit execution time and maintain robustness, it is preferable to select a (preferably small) subset of atlases to be used for(More)
PURPOSE Automated delineation of structures and organs is a key step in medical imaging. However, due to the large number and diversity of structures and the large variety of segmentation algorithms, a consensus is lacking as to which automated segmentation method works best for certain applications. Segmentation challenges are a good approach for unbiased(More)
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