Lennart Bargsten

Lennart Bargsten







 Research Assistant

 +49 (0)40 42878 3547



2018 - today MTEC Institute / TUHH
2017 - 2018 Helmut Schmidt University
2014 - 2017 University of Hamburg (Physics, M.Sc.)
2011 - 2014 TUHH (Mechanical Engineering, B.Sc.)


Deep learning for medical image analysis

  • Focus on ultrasound and computed tomography data (2D, 3D)
  • Particularly interested in methods for performance improvement of deep learning models with limited data
  • Generative adversarial networks for domain adaption and style transfer
  • Ultrasound simulations for data augmentation


  • Research assistant
  • PhD student



  • L. Bargsten, K. A. Riedl, T. Wissel, F. J. Brunner, K. Schaefers, J. Sprenger, M. Grass, M. Seiffert, S. Blankenberg, A. Schlaefer (2021). Tailored methods for segmentation of intravascular ultrasound images via convolutional neural networks. In Brett C. Byram and Nicole V. Ruiter (Eds.) Medical Imaging 2021: Ultrasonic Imaging and Tomography SPIE: 1-7. [Abstract] [doi] [www] [BibTex]


  • M. Seemann, L. Bargsten, A. Schlaefer (2020). Data augmentation for computed tomography angiography via synthetic image generation and neural domain adaptation. Current Directions in Biomedical Engineering. 6 (1), 20200015. [Abstract] [doi] [www] [BibTex]

  • L. Bargsten, A. Schlaefer (2020). SpeckleGAN: a generative adversarial network with an adaptive speckle layer to augment limited training data for ultrasound image processing. International Journal of Computer Assisted Radiology and Surgery. 15 (9), 1427-1436. [Abstract] [doi] [www] [BibTex]


  • F. Sommer, L. Bargsten, A. Schlaefer (2019). IVUS-Simulation for Improving Segmentation Performance of Neural Networks via Data Augmentation. CURAC 2019 Tagungsband Reutlingen 47-51. [Abstract] [www] [BibTex]

  • L. Bargsten, M. Wendebourg, A. Schlaefer (2019). Data Representations for Segmentation of Vascular Structures Using Convolutional Neural Networks with U-Net Architecture. In Proc. 2019 41st IEEE Engineering in Medicine and Biology Society (EMBC'19) Berlin, Germany 989-992. [Abstract] [doi] [www] [BibTex]