Nils Gessert

 

 

 

 

 

 

 Research Assistent

 +49 (0)40 42878 3389

  E.3088

  nils.gesserttuhh.de

2017 - today MTEC Institute / TUHH
2014 - 2016 Northern Institute of Technology Management
2011 - 2017 Hamburg University of Technology

Interests

  • Deep Learning for Medical Image Analysis
  • 3D CNN Architectures for Optical Coherence Tomography (OCT) Data
  • OCT-based Tracking, Force Estimation and Disease Classification
  • Calibration Strategies for OCT with Robotic Systems

Roles

  • Research assistant
  • PhD student

Projects

OCT_principle.png

The principle of Optical Coherence Tomography (OCT). The infrared light-based imaging modality allows for volumetric depth scans with micrometer level resolution.

CNN_principle.png

Deep learning example for OCT. B-Scans can be treated as 2D images and used for training with a CNN.

tracking_example.png

Application example: C-Scans are volumetric data which requires 3D CNN architectures, e.g. for tracking. Thousands of OCT volumes are acquired and labeld with robot poses. The trained CNN can infer the marker's pose from an acquired volume.

force_estimation.png

Application example: Visual deformation of tissue in C-Scans can be used for force estimation. This allows for sensorless haptic feedback in teleoperation.

Member of programm committees and editorial boards

Publications

2018

  • N. Gessert, J. Beringhoff, C. Otte, A. Schlaefer (2018). Force Estimation from OCT Volumes using 3D CNNs. Proceedings, supplement of the International Journal of CARS'2018. accepted. [BibTex]

  • N. Gessert, M. Heyder, S. Latus, M. Lutz, A. Schlaefer (2018). Plaque Classification in Coronary Arteries from IVOCT Images Using Convolutional Neural Networks and Transfer Learning. Proceedings, supplement of the International Journal of CARS'2018 accepted. [BibTex]

  • N. Gessert, M. Schlüter, A. Schlaefer (2018). A Deep Learning Approach for Pose Estimation from Volumetric OCT Data. Medical Image Analysis. 46, 162-179. [doi] [BibTex]

  • S. Latus, S. 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. Medical Imaging 2018: Physics of Medical Imaging 105732E. [doi] [BibTex]

2017

  • K. V. Laino, T. Saathoff, T. R. Savarimuthu, K. Lindberg Schwaner, N. Gessert, A. Schlaefer (2017). Design and implementation of a wireless instrument adapter. 16. Jahrestagung der Deutschen Gesellschaft für Computer- und Roboter Assistierte Chirurgie 31-36. [BibTex]

  • O. Rajput, M. Schlüter, N. Gessert, T. R. Savarimuthu, C. Otte, S.-T. Antoni, A. Schlaefer (2017). Robotic OCT Volume Acquisition Using a Single Fiber. 16. Jahrestagung der Deutschen Gesellschaft für Computer- und Roboter Assistierte Chirurgie 232-233. [BibTex]

Student Theses

In general, I supervise student theses with topics on deep learning for medical problems. In case you are interested in this field, contact me via E-Mail. 

Requirements:

  • Very good academic record
  • Very good programming skills (e.g. Python/Java/C/C++)
  • Background knowledge on machine learning and deep learning
  • Motivation and the ability to think critically and work independently

Please provide in your E-Mail:

  • Bachelor certificate and current transcript of records
  • Curriculum Vitae
  • A short text where you highlight your technical interests and related prior experiences