JANEK GRÖHL
CURRICULUM VITAE
   janekgroehl@live.de
   @jgroehl
   jgroehl

Education

11/2016 - 04/2021 Dr. sc. hum.: German Cancer Research Center (DKFZ) and Heidelberg University
Thesis title: "Data-driven quantitative photoacoustic imaging"
Final grade: summa cum laude
09/2014 – 10/2016 M.Sc. Medical Informatics: Heidelberg University, Heilbronn University, and the
German Cancer Research Center (DKFZ)
Thesis title: "Machine learning-based quantitative photoacoustic imaging"
Final grade: 1,1
09/2011 – 08/2014 B.Sc. Medical Informatics: Heidelberg University & Heilbronn University
Thesis title: "Potential Analysis of Smart Glasses in Dermatology using the example of the Malignant Melanoma"
Final grade: 1,3

Research Experience

Since 02/2022 Walter Benjamin Programme Fellow funded by the German Research Foundation (DFG) at Cancer Research UK, Cambridge Institute, University of Cambridge
Since 07/2022 By-Fellow at Hughes Hall College, University of Cambridge
09/2021 - 09/2022 Honorary Research Assistant at the Department of Medical Physics & Biomedical Engineering at University College London, UK
12/2020 - 01/2022 Research Associate at Bohndieklab, Cancer Research UK, Cambridge Institute
02/2020-11/2020 Postdoctoral Researcher at the German Cancer Research Center (DKFZ) Heidelberg

Teaching Experience

Since 2022 Lecturing on Medical Physics of Ultrasound Imaging for the Royal College of Radiologists
Since 2021 Supervision of research projects of students at the University of Cambridge (Part III Physics projects, MRes Mini Projects, Summer Internships)
09/2020 - 08/2021 Lectureship at Technische Hochschule Ulm (4 credit hours)
2016 - 2020 Supervision of Students at Heidelberg University (Internships, Bachelor theses, Master theses)
06/2012 - 08/2013 Seminar lecture for Mathematics (Analysis I & II) at Heilbronn University of Applied Sciences

Fellowships, Grants, and Awards

02/2022 Postdoctoral fellowship “Walter Benjamin Programme” of the German Research Foundation (DFG)
07/2021 NVIDIA Academic Hardware Grant (2x Quadro RTX 8000 and 1x Quadro RTX NVLink HB 2-Slot)
03/2021 Seal of Excellence by the European commission for project proposal 101023741, “PALPAITINE” submitted under the Horizon 2020’s Marie Skłodowska-Curie actions call H2020-MSCA-IF-2020
07/2018 Best Poster Award: Annual PhD Retreat of the German Cancer Research Center
04/2017 1st prize conhIT Nachwuchspreis 2017 for the master thesis “Machine learning based quantitative photoacoustic tomography” including a presentation at the conhIT 2017 conference
04/2017 Thomas-Gessmann-Special-Award for the master thesis “Machine learning based quantitative photoacoustic tomography”
11/2016 Three-year PhD Stipend of the Helmholz Graduate School for Cancer Research at the German Cancer Research Center
10/2015 Thomas-Gessmann-Award for the outstanding bachelor thesis „Potentialanalyse von SmartGlasses in der Dermatologie am Beispiel des malignen Melanoms“
09/2015 One-year National Stipend of Heilbronn University and Dürr Dental AG
09/2012 Two-year National Stipend of Heilbronn University and the Thomas-Gessmann-Stiftung

Conference Talks and Invited Talks

02/2024 Two talks at SPIE Photonics West 2024
09/2023 Invited Talk: “Data-driven quantitative photoacoustic imaging” Applied Inverse Problems
02/2023 Two talks and a poster at SPIE Photonics West 2023
10/2022 Invited Talk: “Quantitative Photoacoustic Imaging” University of Zurich & ETH Zurich
08/2022 Invited Talk: “Quantitative Photoacoustic Tomography” Kings College London
07/2022 Invited Talk and plenary discussion char “Open Science and Sustainable Software for Data-driven Discovery” British Antarctic Survey
06/2022 Invited Talk: “Software Development with Open Science Principles” Edinburgh Napier University
06/2022 Invited Talk: “Towards data-driven quantitative photoacoustic imaging” Martin-Luther-University Halle-Wittenberg
03/2021 Conference Talk: “International photoacoustic standardisation consortium (IPASC): facilitation of international collaboration by means of a standardised metadata format for photoacoustic images” SPIE Photonics West
04/2020 Invited Talk: “Machine learning-based inference of functional tissue properties from multispectral photoacoustic imaging” at the OSA Biophotonics Congress
04/2020 Conference Talk: “International Photoacoustic Standardisation Consortium (IPASC): Progress in the data acquisition and management theme” SPIE Photonics West
04/2020 Conference Talk: “Deep learning-based oxygenation estimation for multispectral photoacoustic imaging” SPIE Photonics West
11/2019 Invited Talk: “Current Progress of the Data Acquisition and Management Theme” First IPASC Symposium
04/2019 Invited Talk: “Machine learning-based quantitative photoacoustic imaging” at the Biomedical Photonics Seminar at Bern University
03/2019 Conference Talk: “International Photoacoustic Standardisation Consortium (IPASC): recommendations for standardized data exchange in photoacoustic imaging” SPIE Photonics West
12/2018 Invited talk at a satellite event to the German Digital Summit organised by Siemens Healthineers
02/2018 Conference Talk: “Confidence estimation for quantitative photoacoustic imaging” SPIE Photonics West
02/2018 Conference Talk: “Reconstruction of initial pressure from limited view photoacoustic images using deep learning” SPIE Photonics West

Commissions of Trust

02/2023 Session Chair at the Photons Plus Ultrasound conference at SPIE Photonics West 2023
04/2022 Associate Editor for the Journal Medical Physics
Since 2021 Administration of the bohndieklab.org website
Since 2021 Co-lead of an international project on the systematic comparison of image reconstruction algorithms for photoacoustic imaging
Since 2018 Regular reviewing of scientific articles for the following journals: Photoacoustics, IEEE Transactions on Medical Imaging, Journal of Biomedical Optics, Biomedical Optics Express, Applied Sciences, Sensors
Since 2018 Leadership team member of the International Photoacoustic Standardisation Consortium (IPASC) and Co-lead of the Data Acquisition and Management thematic working group
Since 2018 Design and administration of the ipasc.science website

Peer Reviewed Articles

J Gröhl, TR Else, L Hacker, EV Bunce, PW Sweeney, SE Bohndiek. Moving beyond simulation: data-driven quantitative photoacoustic imaging using tissue-mimicking phantoms, IEEE Trans Med Imaging, 2023.
J Gröhl*, L Hacker*, BT Cox, KK Dreher, S Morscher, A Rakotondrainibe, F Varray, LC Yip, WC Vogt, SE Bohndiek and International Photoacoustic Standardisation Consortium. The IPASC data format: A consensus data format for photoacoustic imaging. Photoacoustics, p.100339, 2022. *shared first authorship
M Schellenberg, KK Dreher, N Holzwarth, F Isensee, A Reinke, N Schreck, A Seitel, MD Tizabi, L Maier-Hein* and J Gröhl*. Semantic segmentation of multispectral photoacoustic images using deep learning. Photoacoustics, p.100341, 2022. *shared senior authorship
J Gröhl*, KK Dreher*, M Schellenberg, T Rix, N Holzwarth, P Vieten, L Ayala, SE Bohndiek, A Seitel, and L Maier-Hein. SIMPA: an open-source toolkit for simulation and image processing for photonics and acoustics. Journal of Biomedical Optics, 2022. *shared first authorship
J Gröhl, T Kirchner, TJ Adler, L Hacker, N Holzwarth, A Hernández-Aguilera, MA Herrera, E Santos, SE Bohndiek, and L Maier-Hein. Learned spectral decoloring enables photoacoustic oximetry. Scientific reports, 11(1), pp.1-12, 2021.
J Gröhl, M Schellenberg, KK Dreher, and L Maier-Hein. Deep learning for biomedical photoacoustic imaging: A review. Photoacoustics, p.100241, 2021.
J Gröhl, T Kirchner, TJ Adler, and L Maier-Hein. Confidence estimation for machine learning-based quantitative photoacoustics. Journal of Imaging, 4(12):147, 2018.
T Kirchner*, J Gröhl*, and L Maier-Hein. Context encoding enables machine learning-based quantitative photoacoustics. Journal of biomedical optics, 23(5):056008, 2018. *shared first authorship

Peer Reviewed Co-Authorships

H Assi et al. A review of a strategic roadmapping exercise to advance clinical translation of photoacoustic imaging: From current barriers to future adoption. Photoacoustics, 2023.
L Hacker et al. Fabrication of a Stable, Biologically Relevant Phantom Material. J of Visualized Experiments, 2023.
M Schellenberg et al. Photoacoustic image synthesis with generative adversarial networks. Photoacoustics, 2022.
EL Brown et al. Quantification of vascular networks in photoacoustic mesoscopy. Photoacoustics, 2022.
L Maier-Hein et al. Heidelberg colorectal data set for surgical data science in the sensor operating room. Scientific data, 8(1), pp.1-11, 2021.
T Kirchner et al. Photoacoustics can image spreading depolarization deep in gyrencephalic brain. Scientific reports, 9(1), pp.1-9, 2019.
TJ Adler et al. Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks. International journal of computer assisted radiology and surgery, 14(6), pp.997-1007, 2019.
T Kirchner et al. Se delay multiply and sum beamforming for multispectral photoacoustic imaging. Journal of Imaging, 4(10), p.121, 2018.
M Klemm et al. MITK-OpenIGTLink for combining open-source toolkits in real-time computer-assisted interventions. International journal of computer assisted radiology and surgery, 12(3), pp.351-361, 2017.
N Holzwarth et al. Tattoo tomography: Freehand 3D photoacoustic image reconstruction with an optical pattern. International Journal of Computer Assisted Radiology and Surgery, 16(7), pp.1101-1110, 2021.

Preprints and Conference Proceedings

K Gu, K Yeung, M Doherty, L Hacker, TR Else, SE Bohndiek, J Gröhl. Long-short-term-memory cells enable flexible deep learning-based photoacoustic oximetry. Photons Plus Ultrasound: Imaging and Sensing, 2023.
J Gröhl, L Hacker, BT Cox, International Photoacoustic Standardisation Consortium (IPASC): a structured comparison of photoacoustic image reconstruction algorithms. Photons Plus Ultrasound: Imaging and Sensing, 2022.
J Gröhl, T Kirchner and L Maier-Hein. Confidence estimation for quantitative photoacoustic imaging. In Photons Plus Ultrasound: Imaging and Sensing 2018 (Vol. 10494, p. 104941C). International Society for Optics and Photonics, 2018.
J Gröhl, T Kirchner, T Adler, L Maier-Hein. In silico 2D photoacoustic imaging data [Data Set]. zenodo archive. https://doi.org/10.5281/zenodo.1474258

Preprints and Conference Proceedings Co-Authorships

KK Dreher et al. Unsupervised domain transfer with conditional invertible neural networks. arXiv preprint arXiv:2303.10191, 2023
TR Else et al. The effects of skin tone on photoacoustic imaging and oximetry. bioRxiv, 2023.08. 17.553653, 2023
PW Sweeney et al. Segmentation of 3D blood vessel networks using unsupervised deep learning. bioRxiv, 2023.04. 30.538453, 2023.
P Vieten et al. Deep learning-based semantic segmentation of clinically relevant tissue structures leveraging multispectral photoacoustic images. Photons Plus Ultrasound: Imaging and Sensing, 2022.
JH Nölke et al. Invertible neural networks for uncertainty quantification in photoacoustic imaging. In Bildverarbeitung für die Medizin 2021 (pp. 330-335). Springer, Wiesbaden, 2021.
SE Bohndiek et al. IPASC: A community-driven consensus-based initiative towards standardisation in photoacoustic imaging. In 2020 IEEE International Ultrasonics Symposium (IUS) (pp. 1-4). IEEE, 2020.
TJ Adler et al. Uncertainty handling in intra-operative multispectral imaging with invertible neural networks. In International Conference on Medical Imaging with Deep Learning--Extended Abstract Track, 2019.
LA Ayala et al. Live monitoring of Haemodynamic changes with Multispectral image analysis. In OR 2.0 context-aware operating theaters and machine learning in clinical Neuroimaging (pp. 38-46). Springer, Cham, 2019.
T Kirchner et al. Photoacoustic monitoring of blood oxygenation during neurosurgical interventions. In Photons Plus Ultrasound: Imaging and Sensing 2019 (Vol. 10878, pp. 14-18). SPIE, 2019.
T Kirchner et al. An open-source software platform for translational photoacoustic research and its application to motion-corrected blood oxygenation estimation. arXiv preprint arXiv:1901.09781, 2019.
D Waibel et al. Reconstruction of initial pressure from limited view photoacoustic images using deep learning. In Photons Plus Ultrasound: Imaging and Sensing 2018 (Vol. 10494, p. 104942S). International Society for Optics and Photonics, 2018.
L Maier-Hein et al. Crowd-algorithm collaboration for large-scale endoscopic image annotation with confidence. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 616-623). Springer, Cham, 2016.