Tassilo Wald | German Cancer Research Center (DKFZ) & Helmholtz Imaging

About me

I am currently a Ph.D. student at the German Cancer Research Center (DKFZ) in the division of Medical Image Computing (MIC) under the supervision of Klaus H. Maier-Hein, where I am fortunate to work with great colleagues like Fabian Isensee. Prior, I received my M.Sc. at Karlsruhe Institute of Technology (KIT) in electrical engineering and information theory in 2019, in which I focused on navigation and control theory, before getting involved in perception with deep neural networks.

My research interests focus on understanding machine learning and applying it to medical image analysis – specifically I am interested in understanding what different deep learning networks have in common and where they differ in order to improve robustness of an ensemble and decrease silent failures. More recently, due to the advance of SAM and SEEM, I am interested in unlocking the potential that 3D vision foundation models hold for radiology.

News

[Oct. 2023] Our paper about multi dataset learning was chosen for Oral at MICCAI 2023.
[Oct. 2023] My student Jonathan Deissler & I won the LNQ MICCAI 2023 challenge.
[Jul. 2023] Our paper about representation recycling was accepted to WACV 2024 early.
[Jul. 2023] Our paper about modeling COPD detection as OOD problem was accepted to MICCAI 2023.
[Jul. 2023] Our paper about multi dataset learning was accepted to MICCAI 2023.
[Jul. 2023] I'll be holding two orals at the BVM workshop 2022 about Brain Metastasis segmentation and our AMOS2022 solution.
[Jun. 2023] Our workshop paper about learning diverse representation was accepted at SCIS 2023.
[Apr. 2023] Within a day we wrote a quick evaluation of Meta's SAM for a MIDL short paper.
[Feb. 2023] I joined the Heidelberg AI organizing team.
[Oct. 2022] Fabian Isensee, Constantin Ulrich and I won the AMOS2022 MICCAI challenge.
[Feb. 2022] Two colleagues and I won the "AI-HERO Hackathon for Energy-Efficient AI".

Publications [Google Scholar]

MICCAI

MultiTalent: A Multi-dataset Approach to Medical Image Segmentation.

Constantin Ulrich, Fabian Isensee, Tassilo Wald, Maximilian Zenk, Michael Baumgartner, Klaus H. Maier-Hein

Medical Image Computing and Computer Assisted Intervention - (MICCAI), 2023.

PDF Code Project Page BibTex Oral presentation

MICCAI

cOOpD: Reformulating COPD classification on chest CT scans as anomaly detection using contrastive representations

Silvia D. Almeida^*, Carsten T. Lüth^*, Tobias Norajitra, Tassilo Wald, Marco Nolden, Paul F. Jaeger, Claus P. Heussel, Jürgen Biederer, Oliver Weinheimer, Klaus Maier-Hein

Medical Image Computing and Computer Assisted Intervention - (MICCAI), 2023.

PDF Code Project Page BibTex

WACV

RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement.

Gregor Köhler, Tassilo Wald, Constantin Ulrich, David Zimmerer, Paul F. Jaeger, Jörg K. H. Franke, Simon Kohl, Fabian Isensee, Klaus H. Maier-Hein

IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024.

PDF Project Page BibTex Early accept

SCIS

Exploring new ways: Enforcing representational dissimilarity to learn new features and reduce error consistency

Tassilo Wald, Constantin Ulrich, Fabian Isensee, David Zimmerer, Gregor Koehler, Michael Baumgartner, Klaus H. Maier-Hein

Published at the ICML 2023 Workshop on Spurious Correlations, Invariance, and Stability

PDF Project Page BibTex

BVM

Taming Detection Transformers for Medical Object Detection

Marc K. Ickler^*, Michael Baumgartner^*, Saikat Roy, Tassilo Wald, Klaus H. Maier-Hein

Bildverarbeitung für die Medizin (BVM), 2023.

PDF Project Page BibTex Nominated for Best Paper Award & Oral

MIDL short

SAM.MD: Zero-shot medical image segmentation capabilities of the Segment Anything Model

Saikat Roy^*, Tassilo Wald^*, Gregor Köhler^*, Maximilian R. Rokuss^*, Nico Disch^*, Julius Holzschuh^*, David Zimmerer^*, Klaus H. Maier-Hein

Medical Imaging with Deep Learning (MIDL), short paper track, 2023.

PDF Project Page BibTex

BVM

Extending nnU-Net is all you need

Fabian Isensee^*, Constantin Ulrich^*, Tassilo Wald^*, Maier-Hein Klaus

Bildverarbeitung für die Medizin (BVM), 2023.

PDF Project Page BibTex Technical Report of our 1st place challenge participation in AMOS2022.

NOA

Automated detection and quantification of brain metastases on clinical MRI data using artificial neural networks

Irada Pflueger^*, Tassilo Wald^*, Fabian Isensee, Marianne Schell, Hagen Meredig, Kai Schlamp, Denise Bernhardt, Gianluca Brugnara, Claus Peter Heußel, Juergen Debus, Wolfgang Wick, Martin Bendszus, Klaus H. Maier-Hein, Philip Vollmuth

Neuro-Oncology Advances, 4(1), 2022

PDF Code BibTex

IV

Temporal Feature Networks for CNN based Object Detection

Michael Weber, Tassilo Wald, J. Marius Zollner

IEEE Intelligent Vehicles Symposium, 2021

PDF Project Page BibTex

Challenges & Hackathons

1st place

Challenge: Mediastinal Lymph Node Quantification (LNQ): Segmentation of Heterogeneous CT Data

Jonathan Deissler^*, Tassilo Wald^*

Participating teams: 13

Hosted by: Medical Image Computing and Computer Assisted Intervention - (MICCAI), 2023.

Challenge Leaderboard

1st place

Challenge: Abdominal Multi-Organ Segmentation (AMOS) Challenge 2022

Fabian Isensee^*, Constantin Ulrich^*, Tassilo Wald^*

Participating teams: 20

Hosted by: Medical Image Computing and Computer Assisted Intervention - (MICCAI), 2022.

Challenge Leaderboard Technical Report

1st place

Hackathon: AI-HERO Hackathon for Energy-Efficient AI

Tassilo Wald^*, Michael Baumgartner^*, Gregor Köhler^*

Participating teams: 4

Hosted by: Helmholtz Information & Data Science Academy (HiDA), 2022.

Challenge

Miscellaneous

Contact

Address: Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
Office Location: Forschungszentrum für Bildgebung und Radioonkologie (REZ), F.01.079
Email: tassilo.wald (at) dkfz-heidelberg.de