Mattias P. Heinrich | DeepAI

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∙ 06/29/2023

Unsupervised 3D registration through optimization-guided cyclical self-training

State-of-the-art deep learning-based registration methods employ three d...

0 Alexander Bigalke, et al. ∙

∙ 06/26/2023

A denoised Mean Teacher for domain adaptive point cloud registration

Point cloud-based medical registration promises increased computational ...

0 Alexander Bigalke, et al. ∙

∙ 11/22/2022

Anatomy-guided domain adaptation for 3D in-bed human pose estimation

3D human pose estimation is a key component of clinical monitoring syste...

0 Alexander Bigalke, et al. ∙

∙ 07/01/2022

Adapting the Mean Teacher for keypoint-based lung registration under geometric domain shifts

Recent deep learning-based methods for medical image registration achiev...

0 Alexander Bigalke, et al. ∙

∙ 02/28/2022

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

The majority of current research in deep learning based image registrati...

0 Mattias P. Heinrich, et al. ∙

∙ 01/08/2022

CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwnannoma and Cochlea Segmentation

Domain Adaptation (DA) has recently raised strong interests in the medic...

5 Reuben Dorent, et al. ∙

∙ 12/08/2021

Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning

To date few studies have comprehensively compared medical image registra...

4 Alessa Hering, et al. ∙

∙ 12/06/2021

Fast 3D registration with accurate optimisation and little learning for Learn2Reg 2021

Current approaches for deformable medical image registration often strug...

0 Hanna Siebert, et al. ∙

∙ 03/01/2021

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

As in other areas of medical image analysis, e.g. semantic segmentation,...

0 Lasse Hansen, et al. ∙

∙ 12/05/2020

Development and Characterization of a Chest CT Atlas

A major goal of lung cancer screening is to identify individuals with pa...

0 Kaiwen Xu, et al. ∙

∙ 05/28/2020

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

Multimodal image registration is a very challenging problem for deep lea...

0 Mattias P. Heinrich, et al. ∙

∙ 05/27/2020

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

Though, deep learning based medical image registration is currently star...

0 Lasse Hansen, et al. ∙

∙ 05/26/2020

Learning to map between ferns with differentiable binary embedding networks

Current deep learning methods are based on the repeated, expensive appli...

0 Max Blendowski, et al. ∙

∙ 09/17/2019

Learning Deformable Point Set Registration with Regularized Dynamic Graph CNNs for Large Lung Motion in COPD Patients

Deformable registration continues to be one of the key challenges in med...

0 Lasse Hansen, et al. ∙

∙ 07/25/2019

Closing the Gap between Deep and Conventional Image Registration using Probabilistic Dense Displacement Networks

Nonlinear image registration continues to be a fundamentally important t...

4 Mattias P. Heinrich, et al. ∙

∙ 03/05/2019

FastReg: Fast Non-Rigid Registration via Accelerated Optimisation on the Manifold of Diffeomorphisms

We present a new approach to diffeomorphic non-rigid registration of med...

8 Daniel Grzech, et al. ∙

∙ 02/21/2019

Evaluation of Algorithms for Multi-Modality Whole Heart Segmentation: An Open-Access Grand Challenge

Knowledge of whole heart anatomy is a prerequisite for many clinical app...

14 Xiahai Zhuang, et al. ∙

∙ 09/14/2018

Multi-Kernel Diffusion CNNs for Graph-Based Learning on Point Clouds

Graph convolutional networks are a new promising learning approach to de...

0 Lasse Hansen, et al. ∙

∙ 07/02/2018

Estimation of Large Motion in Lung CT by Integrating Regularized Keypoint Correspondences into Dense Deformable Registration

We present a novel algorithm for the registration of pulmonary CT scans....

0 Jan Rühaak, et al. ∙

∙ 01/29/2018

TernaryNet: Faster Deep Model Inference without GPUs for Medical 3D Segmentation using Sparse and Binary Convolutions

Deep convolutional neural networks (DCNN) are currently ubiquitous in me...

0 Mattias P. Heinrich, et al. ∙

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