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Evaluation of Image Processing Methods for Clinical Applications

Hristina Uzunova; Sandra Schultz; Heinz Handels; Jan Ehrhardt
In: Heinz Handels; Thomas M. Deserno; Andreas Maier; Klaus Hermann Maier-Hein; Christoph Palm; Thomas Tolxdorff (Hrsg.). Bildverarbeitung für die Medizin 2019. Workshop Bildverarbeitung für die Medizin (BVM-2019), March 17-19, Lübeck, Germany, Pages 15-20, ISBN 978-3-658-25326-4, Springer Fachmedien Wiesbaden, 2019.


While developing medical image applications, their accuracy is usually evaluated on a validation dataset, that generally differs from the real clinical data. Since clinical data does not contain ground truth annotations, it is impossible to approximate the real accuracy of the method. In this work, a cGAN-based method to generate realistically looking clinical data preserving the topology and thus ground truth of the validation set is presented. On the example of image registration of brain MRIs, we emphasize the necessity for the method and show that it enables evaluation of the accuracy on a clinical dataset. Furthermore, the topology preserving and realistic appearance of the generated images are evaluated and considered to be sufficient.