Mr. Marcel Bengs Profile

Marcel Bengs

at Technische Univ. Hamburg-Harburg

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Publications (6)

Proceedings Article | 3 April 2023 Poster + Paper

Ultrasound shear wave velocity estimation in a small field of view via spatio-temporal deep learning

Sarah Grube, Marcel Bengs, Maximilian Neidhardt, Sarah Latus, Alexander Schlaefer

Proceedings Volume 12464, 1246425 (2023) https://doi.org/10.1117/12.2653833

KEYWORDS: Acoustic waves, Tissues, Deep learning, Ultrasonography, Error analysis, Education and training, Elasticity, Laparoscopy, Gelatin, Elastography

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Proceedings Article | 4 April 2022 Presentation + Paper

Unsupervised anomaly detection in 3D brain MRI using deep learning with multi-task brain age prediction

Marcel Bengs, Finn Behrendt, Max-Heinrich Laves, Julia Krüger, Roland Opfer, Alexander Schlaefer

Proceedings Volume 12033, 1203314 (2022) https://doi.org/10.1117/12.2608120

KEYWORDS: Computer aided diagnosis and therapy, Machine learning, Computer vision technology, Pattern recognition, Brain, Magnetic resonance imaging, Neuroimaging, Magnetism, Intelligence systems, Diagnostics, Computer programming, 3D scanning, 3D magnetic resonance imaging

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Proceedings Article | 15 February 2021 Presentation + Paper

Medulloblastoma tumor classification using deep transfer learning with multi-scale EfficientNets

Marcel Bengs, Michael Bockmayr, Ulrich Schüller, Alexander Schlaefer

Proceedings Volume 11603, 116030D (2021) https://doi.org/10.1117/12.2580717

KEYWORDS: Tumors, Visualization, Tissues, Convolutional neural networks, Brain

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Proceedings Article | 16 March 2020 Presentation + Paper

Melanoma detection with electrical impedance spectroscopy and dermoscopy using joint deep learning models

Nils Gessert, Marcel Bengs, Alexander Schlaefer

Proceedings Volume 11314, 1131414 (2020) https://doi.org/10.1117/12.2548974

KEYWORDS: Melanoma, Skin, Dielectric spectroscopy, Machine learning, Tumor growth modeling, Performance modeling, Nickel, Systems modeling, Process modeling

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Proceedings Article | 16 March 2020 Presentation + Paper

Spatio-spectral deep learning methods for in-vivo hyperspectral laryngeal cancer detection

Marcel Bengs, Stephan Westermann, Nils Gessert, Dennis Eggert, Andreas O. Gerstner, Nina Mueller, Christian Betz, Wiebke Laffers, Alexander Schlaefer

Proceedings Volume 11314, 113141L (2020) https://doi.org/10.1117/12.2549251

KEYWORDS: In vivo imaging, Tumors, Tissues, Cancer, Convolution, Neck, Head, Tissue optics, Image quality, Diagnostics

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Proceedings Article | 6 March 2020 Presentation

In vivo detection of laryngeal cancer by hyperspectral imaging combined with deep learning methods (Conference Presentation)

Dennis Eggert, Marcel Bengs, Stephan Westermann, Nils Gessert, Andreas O. Gerstner, Nina Müller, Alexander Schlaefer, Christian Betz, Wiebke Laffers

Proceedings Volume 11213, 112130L (2020) https://doi.org/10.1117/12.2557496

KEYWORDS: In vivo imaging, Hyperspectral imaging, Cancer, Tumors, Satellites, Surgery, Tissues, Convolutional neural networks, Convolution

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Showing 5 of 6 publications

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