About me

Modern medicine has made incredible progress in the last 100 years. The development of technology to support medical personnel has contributed to this in particular. It is my wish to do research on data-driven medical technology of tomorrow and to support modern medicine with my contribution. I am a research assistant and fifth year PhD student at the Institute of Mechatronic Systems, Leibniz Universität Hannover, Germany and are currently interested in approximate Bayesian inference for uncertainty-aware medical image analysis. The working title of my PhD thesis is Well-Calibrated Predictive Uncertainty in Medical Imaging with Deep Learning, which I expect to finish by 12/2020.

After finishing my PhD thesis, I take on new challenges and start as a PostDoc at the Institute of Medical Technology and Intelligent Systems with Prof. Alexander Schlaefer.

Experiences

PostDoc

2021 – present
Institute of Medical Technology and Intelligent Systems, Hamburg University of Technology

Further details will be announced soon.

Head of Research Group

2019 – 2020
Institute of Mechatronic Systems, Leibniz Universität Hannover

Medical Technology and Image Processing

PhD Student

2015 – present
Institute of Mechatronic Systems, Leibniz Universität Hannover
  • Thesis working title Well-Calibrated Predictive Uncertainty in Medical Imaging with Deep Learning

Master of Science

2012 - 2015
Leibniz Universität Hannover

Mechanical engineering with focus on robotics and medical image processing

  • Final grade 1.2 (with honours, GPA equiv. 3.8/4.0)
  • Master’s thesis Three-dimensional tracking of soft tissue deformations for incision planning in lasery surgery

Bachelor of Science

2009 - 2012
Leibniz Universität Hannover

Mechanical engineering

  • Bachelor’s thesis Registration of an operating table using the kinect sensor system

Publications

Uncertainty Estimation in Medical Image Denoising with Bayesian Deep Image Prior
Max-Heinrich Laves, Malte Tölle, Tobias Ortmaier
UNSURE Workshop at MICCAI (2020)
Self-Supervised Domain Adaptation for Patient-Specific, Real-Time Tissue Tracking
Sontje Ihler, Felix Kuhnke, Max-Heinrich Laves, Tobias Ortmaier
MICCAI (2020)
Well-Calibrated Regression Uncertainty in Medical Imaging with Deep Learning
Max-Heinrich Laves, Sontje Ihler, Jacob F. Fast, Lüder A. Kahrs, Tobias Ortmaier
Medical Imaging with Deep Learning (2020)
Well-Calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference
Max-Heinrich Laves, Sontje Ihler, Karl-Philipp Kortmann, Tobias Ortmaier
4th workshop on Bayesian Deep Learning (NeurIPS) (2019)
A dataset of laryngeal endoscopic images with comparative study on convolution neural network based semantic segmentation
Max-Heinrich Laves, Jens Bicker, Lüder A. Kahrs, Tobias Ortmaier
International Journal of Computer Assisted Radiology and Surgery (2019)
Volumetric 3D stitching of optical coherence tomography volumes
Max-Heinrich Laves, Lüder A. Kahrs, Tobias Ortmaier
Current Directions in Biomedical Engineering (2018)
Feature tracking for automated volume of interest stabilization on 4D-OCT images
Max-Heinrich Laves, Andreas Schoob, Lüder A. Kahrs, Tom Pfeiffer, Robert Huber, Tobias Ortmaier
SPIE Medical Imaging (2017)
Soft tissue motion tracking with application to tablet-based incision planning in laser surgery
Andreas Schoob, Max-Heinrich Laves, Lüder Alexander Kahrs, Tobias Ortmaier
International Journal of Computer Assisted Radiology and Surgery (2016)

Skills & Proficiency

Python

PyTorch

TensorFlow