activity
20172022
most citedEvaluation of Algorithms for Multi-Modality Whole Heart Segmentation: An Open-Access Grand Challenge

29 citations · 39 across the 9 of their papers we have counts for

collaborators

19 papers

eess.IV2022

Automatic Generation of Synthetic Colonoscopy Videos for Domain Randomization

Abhishek Dinkar Jagtap, Mattias Heinrich, Marian Himstedt

An increasing number of colonoscopic guidance and assistance systems rely on machine learning algorithms which require a large amount of high-quality training data. In order to ens…

cs.CV20223 cited

Voxelmorph++ Going beyond the cranial vault with keypoint supervision and multi-channel instance optimisation

Mattias P. Heinrich, Lasse Hansen

The majority of current research in deep learning based image registration addresses inter-patient brain registration with moderate deformation magnitudes. The recent Learn2Reg med…

cs.CV20211 cited

Deep learning based geometric registration for medical images: How accurate can we get without visual features?

Lasse Hansen, Mattias P. Heinrich

As in other areas of medical image analysis, e.g. semantic segmentation, deep learning is currently driving the development of new approaches for image registration. Multi-scale en…

eess.IV2020

Development and Characterization of a Chest CT Atlas

Kaiwen Xu, Riqiang Gao, Mirza S. Khan +8

A major goal of lung cancer screening is to identify individuals with particular phenotypes that are associated with high risk of cancer. Identifying relevant phenotypes is complic…

cs.CV2020

Unsupervised learning of multimodal image registration using domain adaptation with projected Earth Move's discrepancies

Mattias P Heinrich, Lasse Hansen

Multimodal image registration is a very challenging problem for deep learning approaches. Most current work focuses on either supervised learning that requires labelled training sc…

cs.CV20204 cited

Tackling the Problem of Large Deformations in Deep Learning Based Medical Image Registration Using Displacement Embeddings

Lasse Hansen, Mattias P. Heinrich

Though, deep learning based medical image registration is currently starting to show promising advances, often, it still fells behind conventional frameworks in terms of registrati…