Search Results for author: Sven Koehler

Found 6 papers, 5 papers with code

Self-supervised motion descriptor for cardiac phase detection in 4D CMR based on discrete vector field estimations

1 code implementation13 Sep 2022 Sven Koehler, Tarique Hussain, Hamza Hussain, Daniel Young, Samir Sarikouch, Thomas Pickhardt, Gerald Greil, Sandy Engelhardt

Simultaneously, deep learning-based deformable image registration is able to estimate discrete vector fields which warp one time step of a CMR sequence to the following in a self-supervised manner.

Image Registration

Comparison of Evaluation Metrics for Landmark Detection in CMR Images

4 code implementations25 Jan 2022 Sven Koehler, Lalith Sharan, Julian Kuhm, Arman Ghanaat, Jelizaveta Gordejeva, Nike K. Simon, Niko M. Grell, Florian André, Sandy Engelhardt

In this work, we extended the public ACDC dataset with additional labels of the right ventricular insertion points and compare different variants of a heatmap-based landmark detection pipeline.

Mutually improved endoscopic image synthesis and landmark detection in unpaired image-to-image translation

1 code implementation14 Jul 2021 Lalith Sharan, Gabriele Romano, Sven Koehler, Halvar Kelm, Matthias Karck, Raffaele De Simone, Sandy Engelhardt

In this use case, it is of paramount importance to display objects like needles, sutures or instruments consistent in both domains while altering the style to a more tissue-like appearance.

Translation Unsupervised Image-To-Image Translation

How well do U-Net-based segmentation trained on adult cardiac magnetic resonance imaging data generalise to rare congenital heart diseases for surgical planning?

2 code implementations10 Feb 2020 Sven Koehler, Animesh Tandon, Tarique Hussain, Heiner Latus, Thomas Pickardt, Samir Sarikouch, Philipp Beerbaum, Gerald Greil, Sandy Engelhardt, Ivo Wolf

Our results confirm that current deep learning models can achieve excellent results (left ventricle dice of $0. 951\pm{0. 003}$/$0. 941\pm{0. 007}$ train/validation) within a single data collection.

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