Nils Gessert







 Research Assistent

 +49 (0)40 42878 3389


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


  • 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


  • Research assistant
  • PhD student



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


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


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 only an acuqired volume.


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