DeepMI Lab Members

The DeepMI Lab welcomes people of any race, religion, national origin, gender identity, caregiver and family commitments, political affiliation, sexual orientation, and eligible age or ability.
Martin Reuter
Martin Reuter
Principal Investigator

martin.reuter (at) dzne.de
orcid 0000-0002-2665-9693
gscholar Scholar Citations
twitter @deepmilab
github deepmi

Martin is Assistant Professor of Radiology and of Neurology at Harvard Medical School and the Massachusetts General Hospital (Assistant in Neuroscience, Dept. of Radiology and Dept. of Neurology). He is Director of the Image Analysis (Deep-MI Lab) at the German Center for Neurodegenerative Diseases (DZNE), affiliated to the Martinos Center for Biomedical Imaging and the MIT Computer Science and Artificial Intelligence Lab.

Martin started his career as a PhD student at the Welfenlab, Leibniz University of Hannover, Germany, after graduating (2001) there in mathematics with a second major in computer science and a minor in business informatics. He obtained his PhD (2005) in the area of computational and differential geometry from the department of electrical engineering and computer science with summa cum laude and was awarded a prize for his outstanding scientific accomplishments by the University of Hanover.

Supported by a Feodor-Lynen fellowship of the Alexander von Humboldt Foundation he moved to MIT (2006-08) and contributed novel methods for non-rigid shape analysis and processing, receiving a most cited paper award of the Computer-Aided Design journal for his ground-breaking manuscript on spectral shape analysis (ShapeDNA). Martin then moved to MGH/Harvard Medical School in 2008 and began his independent faculty career as Instructor at HMS in 2009/10 transitioning his focus to more applied medical image analysis topics. He contributed novel methods for unbiased longitudinal image processing of brain MRI and structural shape analysis for computer-aided diagnosis and prognosis. His methods are widely employed as part of the open source FreeSurfer software package to study neurodegeneration and assess disease modifying therapies, e.g., by the Alzheimer’s Disease Neuroimaging Initiative, the Rhineland Study, and other large cohort studies.

After receiving a competitive NIH Career Award (2014) for his research on computational methods for medical image analysis, Martin was appointed Assistant Professor by both the Radiology and the Neurology Departments at Harvard Medical School in 2015. He, further, accepted (2017) the offer to direct the Medical Image Analysis at the German Centerfor Neurodegenerative Diseases (DZNE) in Bonn, Germany. During his career so far, Martin has attracted close to $3 mio worth of 3rd party funding.


David Kügler
David Kügler
Postdoc

david.kuegler (at) dzne.de
orcid 0000-0002-4101-819X
gscholar Scholar Citations
twitter @kueglerd
github dkuegler

David focuses of Learning aspects for Artificial Intelligence in Medicine. He has a strong interest in developing next generation learning strategies for medical imaging with an intrinsic inclusion of geometry and modeling. At DZNE he supports students and PhDs with his Deep Learning and medical image processing experience. As an interdisciplinary researcher, David graduated from RWTH Aachen with a degree in mechanical engineering focusing on learning for control engineering in medical robotics. Since then he worked at the TU Darmstadt as a PhD bringing learning to Computer-Assisted Interventions. In specific his PhD thesis addresses image-guided and electromagnetic tracking for temporal bone surgery.

Current Projects:

Geometry Reconstruction, Interpretability


Kersten Diers
Kersten Diers
Research Associate

kersten.diers (at) dzne.de
github kdiers

Kersten graduated from TU Dresden with a degree in Psychology and University of Heidelberg with a degree in Medical Biometry / Biostatistics. His work is at the intersection of applied methods development and empirical research, with a particular focus on shape analysis and statistical modeling of neuroimaging data.

Current Projects:

Hippocampal Thickness Analysis, Shape Asymmetry, Harmonization, Quality Assessment, Bio-Statistics


Leonie Henschel
Leonie Henschel
Research Associate

leonie.henschel (at) dzne.de
github lehenschel

Leonie graduated from the Bonn-Aachen International Center for Information Technology (b-it) with a degree in Life Science Informatics. Her research focuses on the development of deep learning methods for biomedical image analysis with a focus on brain MRIs. She is interested in machine learning, data science and deep learning. In her free time, Leonie enjoys running, yoga and the great outdoors.

Current Projects:

FastSurfer, High-Res MRI (3T and 7T), Geometric Learning, FCD Detection


Santiago Estrada
Santiago Estrada
PhD Student

santiago.estrada (at) dzne.de
orcid 0000-0003-0339-8870
gscholar Scholar Citations
github santiestrada32

Santiago graduated from Technical University of Munich (TUM) with a degree in Biomedical Computing. His research focuses on the deployment of deep learning methods for quantifying imaging biomarkers in large cohort studies (e.g. Rhineland Study). When not at the lab, Santiago enjoys going to the movies and exploring the city.

Current Projects:

Olfactory Bulb Segmentation, Localized Brain Age Prediction, Automated Tools for Retina Image Analysis


Emad Bahrami-Rad
Emad Bahrami-Rad
Research Associate

emad.bahrami-rad (at) dzne.de
github emadRad

Emad graduated from University of Bonn with a Master’s degree in Computer Science. He is working on the development of deep learning methods for substructure segmentation of Cerebellum, Hypothalamus, Hippocampus, and Amygdala. His research interest includes machine learning, deep learning, and computer vision.

Current Projects:

Subfield Segmentation, MR Reconstruction


Christian Ewert
Christian Ewert
Master Student

christian.ewert (at) dzne.de
github christianewert

Christian is a Master student in Computer Science at University of Bonn. He is interested in Deep Learning and its potential to reveal hidden patterns and relationships in neuroimaging data. In his thesis, he explores ways to apply Deep Learning to fiber-tracking in diffusion-weighted MRI.

Current Projects:

Diffusion Processing, Fiber Tracking


Clemens Pollak
Clemens Pollak
Master Student

clemens.pollak (at) dzne.de
github clepol

Clemens is a Master student in Computer Science at Leibniz University Hanover. He is currently writing his thesis and exploring the world of biomedical imaging. In general Clemens is interested in Deep Learning, Data Science and Software Engineering. Outside of the lab he enjoys windsurfing and hiking.

Current Projects:

MR Motion Tracking


Saikat Roy
Saikat Roy
Master Student

saikat.roy (at) dzne.de
gscholar Scholar Citations
github saikat-roy

Saikat is a Master student in Computer Science at University of Bonn with a focus on Intelligent Systems. He is currently working on his thesis which deals with effectively using 3D deep learning in segmenting neuroimaging data. General interests include machine learning, pattern recognition and deep learning. Beyond his work, he enjoys gaming.

Current Projects:

Fully 3D Segmentation Networks


DeepMI Alumni


Markus Schirmer
Postdoctoral Scientist
2016 - 2020
Subsequent Position:


Sailesh Conjeti, PhD
Postdoctoral Scientist
2017 - 2019
Subsequent Position: Product Manager @ Siemens Healthineers


Christian Wachinger, PhD
Postdoctoral Fellow
2011 - 2016
Subsequent Position: Interim Prof. @ LMU Munich


Dorit Kliemann, PhD
Postdoctoral Fellow
2013 - 2018
Subsequent Position: Assistant Prof. @ U Iowa