M. Sc. Niclas Erben

Photo of Niclas Erben


Ratzeburger Allee 160
23562 Lübeck
Gebäude 64, Raum 83

Email: niclas.erben(at)uni-luebeck.de
Phone: +49 451 31015227
Fax: +49 451 31015204

Short Biography

Niclas Erben, né Bockelmann received his M.Sc. in Medical Engineering Science from the University of Lübeck in early 2020. He joined the Institute of Robotics and Cognitive Systems at the University of Lübeck as a PhD student and research assistant in April 2020. In his work he focuses on the application of signal processing and machine learning of biomedical signals in computer-assisted surgery.

Research Interests

  • Artificial intelligence and machine learning
  • Biomedical signal processing
  • 2D/3D medical image processing

Memberships

German Society for Biomedical Engineering (DGBMT)

2022

Niclas Bockelmann, Daniel Schetelig, M. Bonsanto, Steffen Buschschlüter, and Floris Ernst,
Intelligent ultrasonic-aspirator for CNS/ tumor tissue differentiation -- a feasibility study using machine learning, Köln , 2022.
DOI:10.3205/22dgnc188
File: 22dgnc188
Niclas Bockelmann, Daniel Schetelig, Denise Kesslau, Steffen Buschschlüter, Floris Ernst, and M. Bonsanto,
Toward intraoperative tissue classification: exploiting signal feedback from an ultrasonic aspirator for brain tissue differentiation, International Journal of Computer Assisted Radiology and Surgery , 2022.
DOI:10.1007/s11548-022-02713-0
File: s11548-022-02713-0

2021

Ana Estrada Lugo, Felix Haxthausen, Niclas Bockelmann, and Floris Ernst,
Automatic Segmentation of the Femoral Artery from 2D Ultrasound Images, Infinite Science Publishing GmbH, 2021.
ISBN:9783945954652
Ana Estrada Lugo, Niclas Bockelmann, and Felix Haxthausen,
Sequential U-Net Architecture for Automatic Femoral Artery Segmentation in Ultrasound Images, Current Directions in Biomedical Engineering , vol. 7, no. 1, pp. 158-161, 2021.
DOI:10.1515/cdbme-2021-1034
File: cdbme-2021-1034
Niclas Bockelmann, Denise Kesslau, M. Bonsanto, Steffen Buschschlüter, and Floris Ernst,
Towards machine learning-based tissue differentiation using an ultrasonic aspirator: computer assisted radiology and surgery proceedings of the 35th international Congress and exhibition Munich, Germany, June 21--25, 2021, 2021. pp. 107-108.
DOI:10.1007/s11548-021-02375-4
File: s11548-021-02375-4

2019

Niclas Bockelmann, Jan Graßhoff, Lasse Hansen, Giacomo Bellani, Mattias Heinrich, and Philipp Rostalski,
Deep Learning for Prediction of Diaphragm Activity from the Surface Electromyogram, Current Directions in Biomedical Engineering , vol. 5, no. 1, pp. 17-20, 2019. De Gruyter.
Niclas Bockelmann, Diana Krüger, D.C. Florian Wieland, Berit Zeller-Plumhoff, Niccoló Peruzzi, Silvia Galli, Regine Willumeit-Römer, Fabian Wilde, Felix Beckmann, Jörg Hammel, Julian Moosmann, and Mattias Heinrich,
Sparse Annotations with Random Walks for U-Net Segmentation of Biodegradable Bone Implants in Synchrotron Microtomograms, arXiv preprint arXiv:1908.04173 , 2019.