Design and Development of a Web-based Tool for Inpainting of Dissected Aortae in Angiography Images

Alexander Prutsch

Supervisor(s): Antonio Pepe, Jan Egger

TU Graz

Abstract: Medical imaging is an important tool for the diagnosis and the evaluation of an aortic dissection (AD); a serious condition of the aorta, which could lead to a life-threatening aortic rupture. AD patients need life-long medical monitoring of the aortic enlargement and of the disease progression, subsequent to the diagnosis of the aortic dissection. Since there is a lack of “healthy-dissected” image pairs from medical studies, the application of inpainting techniques offers an alternative source for generating them by doing a virtual regression from dissected aortae to healthy aortae; an indirect way to study the origin of the disease. The proposed inpainting tool combines a neural network, which was trained on the task of inpainting aortic dissections, with an easy-to-use user interface. To achieve this goal, the inpainting tool has been integrated within the 3D medical image viewer of StudierFenster ( By designing the tool as a web application, we simplify the usage of the neural network and reduce the initial learning curve.
Keywords: Computer Vision, Human-Computer Interaction, Image Processing, Scientific Visualization
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Year: 2020