48 citations · 82 across the 7 of their papers we have counts for
9 papers
nnFoundation: 3D Foundation Models for Radiology
Constantin Ulrich Harsy, Tassilo Wald, Karol Gotkowski +80
Radiological artificial intelligence has advanced rapidly, yet most systems remain narrowly task-specific, data-intensive, and fragile under domain shift. Foundation models promise…
Towards Integrating Epistemic Uncertainty Estimation into the Radiotherapy Workflow
Marvin Tom Teichmann, Manasi Datar, Lisa Kratzke +2
The precision of contouring target structures and organs-at-risk (OAR) in radiotherapy planning is crucial for ensuring treatment efficacy and patient safety. Recent advancements i…
End-to-end Learning for Image-based Detection of Molecular Alterations in Digital Pathology
Marvin Teichmann, Andre Aichert, Hanibal Bohnenberger +2
Current approaches for classification of whole slide images (WSI) in digital pathology predominantly utilize a two-stage learning pipeline. The first stage identifies areas of inte…
Large Scale Joint Semantic Re-Localisation and Scene Understanding via Globally Unique Instance Coordinate Regression
Ignas Budvytis, Marvin Teichmann, Tomas Vojir +1
In this work we present a novel approach to joint semantic localisation and scene understanding. Our work is motivated by the need for localisation algorithms which not only predic…
Detect-to-Retrieve: Efficient Regional Aggregation for Image Search
Marvin Teichmann, Andre Araujo, Menglong Zhu +1
Retrieving object instances among cluttered scenes efficiently requires compact yet comprehensive regional image representations. Intuitively, object semantics can help build the i…
Convolutional CRFs for Semantic Segmentation
Marvin T. T. Teichmann, Roberto Cipolla
For the challenging semantic image segmentation task the most efficient models have traditionally combined the structured modelling capabilities of Conditional Random Fields (CRFs)…
Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery
Sebastian Bodenstedt, Max Allan, Anthony Agustinos +17
Intraoperative segmentation and tracking of minimally invasive instruments is a prerequisite for computer- and robotic-assisted surgery. Since additional hardware like tracking sys…
MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving
Marvin Teichmann, Michael Weber, Marius Zoellner +2
While most approaches to semantic reasoning have focused on improving performance, in this paper we argue that computational times are very important in order to enable real time a…
Pixel-wise Segmentation of Street with Neural Networks
Sebastian Bittel, Vitali Kaiser, Marvin Teichmann +1
Pixel-wise street segmentation of photographs taken from a drivers perspective is important for self-driving cars and can also support other object recognition tasks. A framework c…