no code implementations • 23 Jan 2024 • Chang Liu, Laura Klein, Yixing Huang, Edith Baader, Michael Lell, Marc Kachelrieß, Andreas Maier
The average organ dice of the proposed method is 0. 71 compared with 0. 63 in baseline model, indicating the enhancement of anatomical structures.
no code implementations • 7 Dec 2020 • Chang Liu, Yixing Huang, Joscha Maier, Laura Klein, Marc Kachelrieß, Andreas Maier
For organ-specific AEC, a preliminary CT reconstruction is necessary to estimate organ shapes for dose optimization, where only a few projections are allowed for real-time reconstruction.
no code implementations • 19 Dec 2019 • Andreas Kofler, Markus Haltmeier, Tobias Schaeffter, Marc Kachelrieß, Marc Dewey, Christian Wald, Christoph Kolbitsch
In this paper we present a generalized Deep Learning-based approach for solving ill-posed large-scale inverse problems occuring in medical image reconstruction.
no code implementations • 15 Oct 2017 • Shuqing Chen, Holger Roth, Sabrina Dorn, Matthias May, Alexander Cavallaro, Michael M. Lell, Marc Kachelrieß, Hirohisa ODA, Kensaku MORI, Andreas Maier
In this paper, we proposed a 3D FCN based method for automatic multi-organ segmentation in DECT.