Výsledky vyhledávání - "Hensen, Bennet"

Akademický článek

Generating Contrast-Enhanced Liver MRI Images from Native Sequences

Autor: Hürtgen Janine, Hille Georg, Saalfeld Sylvia, Kreher Robert, Hensen Bennet, Wacker Frank, Rose Georg, Ringe Kristina I.

Publikováno v: Current Directions in Biomedical Engineering, Vol 10, Iss 1, Pp 33-36 (2024)

Generating synthetic contrast-enhanced liver MRI scans from native MRI images can serve to mitigate the issue of sparse contrast-enhanced image datasets while concurrently circumventing the time-consuming and costly process of administering contrast

Externí odkaz: https://doaj.org/article/36b4f367e54242fb985406d13dca637a

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Akademický článek

Vacuum-based and body-mounted robotic-patient interface with an integrated metasurface for MRI-guided interventions

Autor: Vogt Ivan, Engel Nico, Eisenmann Marcel, Odenbach Robert, Kowal Robert, Düx Daniel, Hensen Bennet, Gutberlet Marcel, Wacker Frank, Rose Georg

Publikováno v: Current Directions in Biomedical Engineering, Vol 10, Iss 1, Pp 93-96 (2024)

The increased clinical relevance of image-guided procedures, particularly of interventional magnetic resonance imaging (iMRI), highlights the need for advanced devices and robotics to optimize those procedures. To enable a realistic integration of ro

Externí odkaz: https://doaj.org/article/13dfa316d27842b98742b07c34b7f6d9

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Liver Segmentation in Time-resolved C-arm CT Volumes Reconstructed from Dynamic Perfusion Scans using Time Separation Technique

Autor: Chatterjee, Soumick, Haseljić, Hana, Frysch, Robert, Kulvait, Vojtěch, Semshchikov, Vladimir, Hensen, Bennet, Wacker, Frank, Brüschx, Inga, Werncke, Thomas, Speck, Oliver, Nürnberger, Andreas, Rose, Georg

Publikováno v: 2022 IEEE 5th International Conference on Image Processing Applications and Systems (IPAS)

Perfusion imaging is a valuable tool for diagnosing and treatment planning for liver tumours. The time separation technique (TST) has been successfully used for modelling C-arm cone-beam computed tomography (CBCT) perfusion data. The reconstruction c

Externí odkaz: http://arxiv.org/abs/2302.04585

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Liver Segmentation using Turbolift Learning for CT and Cone-beam C-arm Perfusion Imaging

Autor: Haseljić, Hana, Chatterjee, Soumick, Frysch, Robert, Kulvait, Vojtěch, Semshchikov, Vladimir, Hensen, Bennet, Wacker, Frank, Brüsch, Inga, Werncke, Thomas, Speck, Oliver, Nürnberger, Andreas, Rose, Georg

Publikováno v: Computers in Biology and Medicine (2023) 106539

Model-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT). To apply TST using prior knowledge extracted from CT perfusion data

Externí odkaz: http://arxiv.org/abs/2207.10167

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Application of Time Separation Technique to Enhance C-arm CT Dynamic Liver Perfusion Imaging

Autor: Haseljić, Hana, Kulvait, Vojtěch, Frysch, Robert, Hensen, Bennet, Wacker, Frank, Rose, Georg, Werncke, Thomas

Publikováno v: Published in Proceedings of the 16th Virtual International Meeting on Fully 3D Image Reconstruction in Radiology and Nuclear Medicine 2021 arXiv:2110.04143

Perfusion imaging is an interesting new modality for evaluation and assessment of the liver cancer treatment. C-Arm CT provides a possibility to perform perfusion imaging scans intra-operatively for even faster evaluation. The slow speed of the C-Arm

Externí odkaz: http://arxiv.org/abs/2110.14318

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2.5D Thermometry Maps for MRI-guided Tumor Ablation

Autor: Alpers, Julian, Reimert, Daniel L., Rötzer, Maximilian, Gerlach, Thomas, Gutberlet, Marcel, Wacker, Frank, Hensen, Bennet, Hansen, Christian

Publikováno v: 24th International Conference on Medical Image Computing and Computer-Assisted Intervention (2021) 311-320

Fast and reliable monitoring of volumetric heat distribution during MRI-guided tumor ablation is an urgent clinical need. In this work, we introduce a method for generating 2.5D thermometry maps from uniformly distributed 2D MRI phase images rotated

Externí odkaz: http://arxiv.org/abs/2108.05734

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