Martin Gromniak

Martin Gromniak

 

 

 

 

 

 

 Research Assistant

 +49 (0)40 42878 3828

  E.3088

  martin.gromniaktuhh.de

2018 - today Technical University of Hamburg (TUHH)
MTEC Institute
2015 - 2018 Technical University of Munich (TUM)
M.Sc. Robotics, Cognition, Intelligence
2011 -2015 Ruhr University Bochum (RUB)
B.Sc. Mechanical Engineering

Interests

  • Deep Learning for Medical Imaging
  • Pose estimation and Tracking methods
  • OCT-based Tracking
  • Robot Control for Force Feedback

Roles

  • Research assistant
  • PhD student

Student Theses

In case you are interested to write a student thesis in one of my research topics, please contact me via E-Mail. 

Requirements:

  • Very good academic record
  • Very good programming skills (e.g. Python/C/C++)
  • 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

Publications

2020

  • M. Gromniak, M. Neidhardt, A. Heinemann, K. Püschel, A. Schlaefer (2020). Needle placement accuracy in CT-guided robotic post mortem biopsy. Current Directions in Biomedical Engineering. 6 (1), 20200031. [Abstract] [doi] [www] [BibTex]

  • M. Gromniak, N. Gessert, T. Saathoff, A. Schlaefer (2020). Needle tip force estimation by deep learning from raw spectral OCT data. International Journal of Computer Assisted Radiology and Surgery. 15 1699-1702. [Abstract] [doi] [www] [BibTex]

  • M. Schlüter, L. Glandorf, M. Gromniak, T. Saathoff, A. Schlaefer (2020). Concept for Markerless 6D Tracking Employing Volumetric Optical Coherence Tomography. Sensors. 20 (9), 2678. [Abstract] [doi] [BibTex]

  • M. Schlüter, L. Glandorf, J. Sprenger, M. Gromniak, M. Neidhardt, T. Saathoff, A. Schlaefer (2020). High-Speed Markerless Tissue Motion Tracking Using Volumetric Optical Coherence Tomography Images. IEEE International Symposium on Biomedical Imaging 1979-1982. [Abstract] [doi] [BibTex]

2019

  • M. Gromniak, C. Brendes, A. Schlaefer (2019). A New Setup for Markerless Motion Compensation in TMS by Relative Head Tracking with a Small-Scale TOF Camera. CURAC 2019 Tagungsband Reutlingen 205-210. [Abstract] [www] [BibTex]

  • N. Gessert, M. Gromniak, M. Bengs, L. Matthäus, A. Schlaefer (2019). Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels. CURAC 2019 Tagungsband Reutlingen 176-180. [Abstract] [www] [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]

  • O. Rajput*, N. Gessert*, M. Gromniak, L. Matthäus, A. Schlaefer (2018). Towards Head Motion Compensation Using Multi-Scale Convolutional Neural Networks. 17. Jahrestagung der Deutschen Gesellschaft für Computer- und Roboter Assistierte Chirurgie 138-141 *Shared First Authors . [Abstract] [www] [BibTex]