• K. P. Abdolazizi, K. Linka, J. Sprenger, M. Neidhardt, A. Schlaefer, C. J. Cyron (2021). Identification of the concentration‐dependent viscoelastic constitutive parameters of gelatin by combining computational mechanics, machine learning. Proceedings in applied mathematics, mechanics. 21. (1), e202100250 [Abstract] [www] [BibTex]

  • G. A. Holzapfel, K. Linka, S. Sherifova, C. J. Cyron (2021). Predictive constitutive modelling of arteries by deep learning. Journal of The Royal Society Interface. 18 (182), 20210411. [Abstract] [doi] [www] [BibTex]

  • S. Lehmann, A. Rogalla, M. Neidhardt, A. Schlaefer, S. Schupp (2021). Online Strategy Synthesis for Safe, Optimized Control of Steerable Needles. Electronic Proceedings in Theoretical Computer Science. 348 128-135. [Abstract] [doi] [www] [BibTex]

  • M. Neidhardt, J. Ohlsen, N. Hoffmann, A. Schlaefer (2021). Parameter Identification for Ultrasound Shear Wave Elastography Simulation:. Current Directions in Biomedical Engineering. 7 (1), 35-38. [Abstract] [doi] [www] [BibTex]

  • K. Linka, M. Hillgärtner, K. P. Abdolazizi, R. C. Aydin, M. Itskov, C. J. Cyron (2021). Constitutive artificial neural networks: A fast and general approach to predictive data-driven constitutive modeling by deep learning. Journal of Computational Physics. 429 110010. [Abstract] [doi] [www] [BibTex]

  • K. P. Abdolazizi, K. Linka, J. Sprenger, M. Neidhardt, A. Schlaefer, C. J. Cyron (2021). Concentration-Specific Constitutive Modeling of Gelatin Based on Artificial Neural Networks. PAMM. 20 (1), e202000284. [Abstract] [doi] [www] [BibTex]

  • S. Latus, J. Sprenger, M. Neidhardt, J. Schädler, A. Ron, A. Fitzek, M. Schlüter, P. Breitfeld, A. Heinemann, K. Püschel, A. Schlaefer (2021). Rupture detection during needle insertions using complex OCT data and CNNs. IEEE Transactions on Biomedical Engineering accepted. [Abstract] [BibTex]

  • J. Ohlsen, M. Neidhardt, A. Schlaefer, N. Hoffmann (2021). Modelling shear wave propagation in soft tissue surrogates using a finite element- and finite difference method. PAMM. 20 (1), e202000148. [Abstract] [doi] [www] [BibTex]


  • A. Rogalla, T. Kamph, U. Bulmann, K. Billerbeck, Blumreiter, S. Schupp (2020). Designing And Analyzing Open Application-Oriented Labs in Software-Verification Education Annual Conference of European Society for Engineering Education (SEFI) Enschede (the Netherlands) 444-453. [Abstract] [BibTex]

  • N. Gessert, M. Bengs, M. Schlüter, A. Schlaefer (2020). Deep learning with 4D spatio-temporal data representations for OCT-based force estimation. Medical Image Analysis. 64 (101730), [Abstract] [doi] [www] [BibTex]

  • A. Rogalla, S. Lehmann, M. Neidhardt, J. Sprenger, M. Bengs, A. Schlaefer, S. Schupp (2020). Synthesizing Strategies for Needle Steering in Gelatin Phantoms. Models for Formal Analysis of Real Systems (MARS 2020) [Abstract] [doi] [www] [BibTex]

  • S. Latus, P. Breitfeld, M. Neidhardt, W. Reip, C. Zöllner, A. Schlaefer (2020). Boundary prediction during epidural punctures based on OCT relative motion analysis. EUR J ANAESTH. 2020 (Volume 37 | e-Supplement 58 | June 2020), [Abstract] [BibTex]

  • M. Neidhardt, M. Bengs, S. Latus, M. Schlüter, T. Saathoff, A. Schlaefer (2020). 4D Deep learning for real-time volumetric optical coherence elastography. International Journal of Computer Assisted Radiology and Surgery 2020 1861-6429. [Abstract] [doi] [www] [BibTex]

  • M. Neidhardt, M. Bengs, S. Latus, M. Schlüter, T. Saathoff, A. Schlaefer (2020). Deep Learning for High Speed Optical Coherence Elastography. IEEE International Symposium on Biomedical Imaging 1583-1586. [Abstract] [doi] [BibTex]


  • N. Gessert, M. Gromniak, M. Schlüter, A. Schlaefer (2019). Two-path 3D CNNs for calibration of system parameters for OCT-based motion compensation. SPIE Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling. 1095108. [www][doi] [BibTex]


  • N. Gessert, T. Priegnitz, T. Saathoff, S.-T. Antoni, D. Meyer, M. F. Hamann, K.-P. Jünemann, C. Otte, A. Schlaefer (2018). Needle Tip Force Estimation using an OCT Fiber and a Fused convGRU-CNN Architecture - MICCAI 2018. International Conference on Medical Image Computing and Computer-Assisted Intervention 222-229, Spotlight Talk. [Abstract] [www] [BibTex]


  • S. Latus, C. Otte, M. Schlüter, J. Rehra, K. Bizon, H. Schulz-Hildebrandt, T. Saathoff, G. Hüttmann, A. Schlaefer (2017). An Approach for Needle Based Optical Coherence Elastography Measurements. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2017. 655-663. [Abstract] [doi] [www] [BibTex]