Clinical navigation is largely based on image data and we focus on fast image modalities allowing for feedback and control. Particularly, we study optical coherence tomography (OCT) for precise, high resolution image guidance, e.g., in soft tissue and cardiac interventions. In addition we are interested in ultrasound (US) as a complementary modality for soft tissue imaging. We study methods to estimate tissue properties from OCT and US, e.g., to obtain forces and elasticity, and we integrate image guidance with robotics, navigation and machine learning.

Selected publications

N. Gessert, S. Latus, Y. S. Abdelwahed, D. M. Leistner, M. Lutz, A. Schlaefer (2019). Bioresorbable Scaffold Visualization in IVOCT Images Using CNNs and Weakly Supervised Localization. SPIE Medical Imaging 2019: Image Processing. Accepted.

N. Gessert, J. Beringhoff, C. Otte, A. Schlaefer (2018). Force Estimation from OCT Volumes using 3D CNNs. Int J Comput Assist Radiol Surg. 13 (7), 1073–1082.

S. Latus, F. Griese, M. Gräser, M. Möddel, M. Schlüter, C. Otte, N. Gessert, T. Saathoff, T. Knopp, A. Schlaefer (2018). Towards bimodal intravascular OCT MPI volumetric imaging. Proceedings of SPIE Medical Imaging: Physics of Medical Imaging 10573E.

R. Berndt, R. Rusch, L. Hummitzsch, M. Lutz, K. Heß, K. Huenges, B. Panholzer, C. Otte, A. Haneya, G. Lutter, A. Schlaefer, J. Cremer, J. Groß (2017). Development of a new catheter prototype for laser thrombolysis under guidance of optical coherence tomography (OCT): validation of feasibility and efficacy in a preclinical model. Journal of Thrombosis and Thrombolysis. 43 (3), 352-360.

O. Shahin, A. Beširevic, M. Kleemann, A. Schlaefer (2014). Ultrasound-based tumor movement compensation during navigated laparoscopic liver interventions. Surg Endosc. 28 (5), 1734-1741.

Motion, i.e., autonomic, active or pathological, is an important aspect that has to be considered when working with people. Predicting and compensating for autonomic motion is important for the quality of many applications like radiosurgery or transcranial magnetic stimulation. In addition, imaging quality can typically be improved if the motive's motion is known and compensated for. This is especially true for (bio-)medical imaging modalities like fluorescence microscopy and intravascular optical coherence tomography which picture very small structures.

We develop algorithms and systems to identify, predict, measure and finally compensate for motion. In addition, we study the reliability, robustness and treatment quality of existing and new methods.

Respiratory Motion Compensation for Robotic Radiosurgery

Motion Compensation of the Head

Motion Compensation for Intravascular Optical Coherence Tomography

Cell motion compensation for fluorescence microscopy

When studying intra-cellular structures over longer time frames, i.e., propagation of calcium signals, knowing the motion as well as the deformation of the cell is of great importance for a detailed signal analysis.

We develop methods to analyze the motion and deformation of cells in order to compensate for this during analysis.

References

  • O. Rajput, S.-T. Antoni, C. Otte, T. Saathoff, L. Matthäus, A. Schlaefer (2016). High Accuracy 3D Data Acquisition Using Co-Registered OCT and Kinect. 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems Baden-Baden [www] [BibTex]

  • S.-T. Antoni, J. Rinast, X. Ma, S. Schupp, A. Schlaefer (2016). Online model checking for monitoring surrogate based respiratory motion tracking in radiation therapy. CARS 2016 Proceedings, supplement of the International Journal of CARS accepted. [Abstract] [BibTex]

  • S.-T. Antoni, X. Ma, S. Schupp, A. Schlaefer (2016). Reducing false discovery rates for on-line model-checking based detection of respiratory motion artifacts. Gemeinsamer Tagungsband der Workshops der Tagung Software Engineering 2016 (SE 2016), Wien, Feb. 2016. [Abstract] [BibTex]

  • A. Tack, Y. Kobayashi, T. Gauer, A. Schlaefer, R. Werner (2015). Groupwise Registration for Robust Motion Field Estimation in Artifact-Affected 4D CT Images.. Workshop on Imaging and Computer Assistance in Radiation Therapy, MICCAI 2015 [BibTex]

  • D. Schetelig, I. M.A. Wolf , B.-P. Diercks, R. Fliegert, A. H. Guse, A. Schlaefer, R. Werner (2015). A Modular Framework for Post-Processing and Analysis of Fluorescence Microscopy Image Sequences of Subcellular Calcium Dynamics. Bildverarbeitung für die Medizin 2015, Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 15. bis 17. März 2015 in Lübeck Springer: 401-406. [Abstract] [doi] [BibTex]

  • S.-T. Antoni, A. Dabrowski, D. Schetelig, B.-P. Diercks, R. Fliegert, R. Werner, I. Wolf, A. H. Guse, A. Schlaefer (2015). Segmentation of T-cells in fluorescence microscopy. In Proc. IEEE Engineering in Medicine and Biology Society (EMBC'15) Milan, Italy [Abstract] [www] [BibTex]

  • S.-T. Antoni, J. Rinast, S. Schupp, A. Schlaefer (2015). Comparing Model-free Motion Prediction and On-line Model Checking for Respiratory Motion Management. Gemeinsamer Tagungsband der Workshops der Tagung Software Engineering Dresden, Germany 15-18. [Abstract] [www] [BibTex]

  • S.-T. Antoni, J. Rinast, S. Schupp, A. Schlaefer (2015). Evaluation des Einflusses von Artefakten auf den Korrelationsfehler in der bewegungskompensierten Radiochirurgie. Tagungsband der 14. Jahrestagung der Deutschen Gesellschaft für Computer- und Roboterassistierte Chirurgie Bremen, Germany 133-138. [Abstract] [BibTex]

  • S.-T. Antoni, R. Plagge, R. Dürichen, A. Schlaefer (2015). Detecting Respiratory Artifacts from Video Data. In Handels, Heinz and Deserno, Thomas Martin and Meinzer, Hans-Peter and Tolxdorff, Thomas (Eds.) Bildverarbeitung für die Medizin 2015 Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 15. bis 17. März 2015 in Lübeck Springer Berlin Heidelberg: 227-232. [Abstract] [doi] [www] [BibTex]

  • N. Lessmann, D. Drömann, A. Schlaefer, (2014). Feasibility of respiratory motion-compensated stereoscopic X-ray tracking for bronchoscopy. Int J Comput Assist Radiol Surg. 9 (2), 199-209. [doi] [BibTex] [pmid]

  • O. Shahin, A. Beširevi?, M. Kleemann, A. Schlaefer (2014). Ultrasound-based tumor movement compensation during navigated laparoscopic liver interventions. Surg Endosc. 28 (5), 1734-1741. [doi] [BibTex]

  • R. Dürichen, T. Wissel, F. Ernst, A. Schlaefer, A. Schweikard (2014). Multivariate respiratory motion prediction. Phys Med Biol. 59 (20), 6043-6060. [doi] [BibTex]

  • B. Stender, F. Ernst, B. Wang, Z. X. Zhang, A. Schlaefer (2013). Motion compensation of optical mapping signals from isolated beating rat hearts. SPIE. (Applications of Digital Image Processing XXXVI, SPIE), 88561C-1 - 88561C-6. [BibTex]

  • F. Ernst, R. Dürichen, A. Schlaefer, A. Schweikard (2013). Evaluating and comparing algorithms for respiratory motion prediction. Phys Med Biol. 58 (11), 3911-3929. [doi] [BibTex]

  • N. Lessmann, D. Drömann, A. Schlaefer (2013). Feasibility of respiratory motion compensated stereoscopic bronchoscopy. [BibTex]

  • R. Dürichen, O. Blanck, J. Dunst, G. Hildebrandt, A. Schlaefer, A. Schweikard (2013). Atemphasenabhängige Prädiktionsfehler in der extrakraniellen stereotaktischen Strahlentherapie. [BibTex]