Publications

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13 Publications visible to you, out of a total of 13

Abstract

Not specified

Authors: Thomas van de Kamp, Achim H. Schwermann, Tomy dos Santos Rolo, Philipp D. Lösel, Thomas Engler, Walter Etter, Tomáš Faragó, Jörg Göttlicher, Vincent Heuveline, Andreas Kopmann, Bastian Mähler, Thomas Mörs, Janes Odar, Jes Rust, Nicholas Tan Jerome, Matthias Vogelgesang, Tilo Baumbach, Lars Krogmann

Date Published: 1st Dec 2018

Publication Type: Journal

Abstract

Not specified

Authors: Wolfgang Mexner, Matthias Bonn, Andreas Kopmann, Viktor Mauch, Doris Ressmann, Suren A. Chilingaryan, Nicholas Tan Jerome, Thomas Van De Kamp, Vincent Heuveline, Philipp Lösel, et al.

Date Published: 2018

Publication Type: Journal

Abstract

Not specified

Authors: Wolfgang Mexner, Matthias Bonn, Andreas Kopmann, Viktor Mauch, Doris Ressmann, Suren A Chilingaryan, Nicholas Tan Jerome, Thomas van de Kamp, Vincent Heuveline, Philipp Lösel

Date Published: 2018

Publication Type: InCollection

Abstract

Not specified

Authors: Sebastian Schmelzle, Thomas van de Kamp, Michael Heethoff, Vincent Heuveline, Philipp Lösel, Jürgen Becker, Felix Beckmann, Frank Schluenzen, Jörg U. Hammel, Andreas Kopmann, Wolfgang Mexner, Matthias Vogelgesang, Nicholas T. Jerome, Oliver Betz, Rolf Beutel, Benjamin Wipfler, Alexander Blanke, Steffen Harzsch, Marie Hörnig, Tilo Baumbach

Date Published: 7th Sep 2017

Publication Type: InProceedings

Abstract

Not specified

Authors: Simon Gawlok, Philipp Gerstner, Saskia Haupt, Vincent Heuveline, Jonas Kratzke, Philipp Lösel, Katrin Mang, Mareike Schmidtobreick, Nicolai Schoch, Nils Schween, Jonathan Schwegler, Chen Song, Martin Wlotzka

Date Published: 2017

Publication Type: Journal

Abstract (Expand)

Segmenting the blood pool and myocardium from a 3D cardiovascular magnetic resonance (CMR) image allows to create a patient-specific heart model for surgical planning in children with complex congenital heart disease (CHD). Implementation of semi-automatic or automatic segmentation algorithms is challenging because of a high anatomical variability of the heart defects, low contrast, and intensity variations in the images. Therefore, manual segmentation is the gold standard but it is labor-intensive. In this paper we report the set-up and results of a highly scalable semi-automatic diffusion algorithm for image segmentation. The method extrapolates the information from a small number of expert manually labeled reference slices to the remaining volume. While results of most semi-automatic algorithms strongly depend on well-chosen but usually unknown parameters this approach is parameter-free. Validation is performed on twenty 3D CMR images.

Authors: Philipp Lösel, Vincent Heuveline

Date Published: 2017

Publication Type: InCollection

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