Håkan Ahlström

According to our database, Håkan Ahlström authored at least 16 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Automatic segmentation of large-scale CT image datasets for detailed body composition analysis.

Nouman Ahmad, Robin Strand, Björn Sparresäter, Sambit Tarai, Elin Lundström, Göran Bergström, Håkan Ahlström, Joel Kullberg

BMC Bioinform., December, 2023

Leveraging point annotations in segmentation learning with boundary loss.

Eva Breznik, Hoel Kervadec, Filip Malmberg, Joel Kullberg, Håkan Ahlström, Marleen de Bruijne, Robin Strand

CoRR, 2023

Introducing Spatial Context in Patch-Based Deep Learning for Semantic Segmentation in Whole Body MRI.

Eva Breznik, Joel Kullberg, Håkan Ahlström, Robin Strand

Proceedings of the Image Analysis - 22nd Scandinavian Conference, 2023

2021

MIMIR: Deep Regression for Automated Analysis of UK Biobank Body MRI.

Taro Langner, Andrés Martínez Mora, Robin Strand, Håkan Ahlström, Joel Kullberg

CoRR, 2021

Deep regression for uncertainty-aware and interpretable analysis of large-scale body MRI.

Taro Langner, Robin Strand, Håkan Ahlström, Joel Kullberg

CoRR, 2021

Uncertainty-aware body composition analysis with deep regression ensembles on UK Biobank MRI.

Taro Langner, Fredrik K. Gustafsson, Benny Avelin, Robin Strand, Håkan Ahlström, Joel Kullberg

Comput. Medical Imaging Graph., 2021

2020

Identifying Morphological Indicators of Aging With Neural Networks on Large-Scale Whole-Body MRI.

Taro Langner, Johan Wikström, Tomas Bjerner, Håkan Ahlström, Joel Kullberg

IEEE Trans. Medical Imaging, 2020

Kidney segmentation in neck-to-knee body MRI of 40, 000 UK Biobank participants.

Taro Langner, Andreas Östling, Lukas Maldonis, Albin Karlsson, Daniel Olmo, Dag Lindgren, Andreas Wallin, Lowe Lundin, Robin Strand, Håkan Ahlström, Joel Kullberg

CoRR, 2020

Large-scale biometry with interpretable neural network regression on UK Biobank body MRI.

Taro Langner, Håkan Ahlström, Joel Kullberg

CoRR, 2020

Fast graph-cut based optimization for practical dense deformable registration of volume images.

Simon Ekström, Filip Malmberg, Håkan Ahlström, Joel Kullberg, Robin Strand

Comput. Medical Imaging Graph., 2020

Recent advances in large scale whole body MRI image analysis: Imiomics.

Robin Strand, Simon Ekström, Eva Breznik, Therese Sjöholm, Martino Pilia, Lars Lind, Filip Malmberg, Håkan Ahlström, Joel Kullberg

Proceedings of the SIET '20: 5th International Conference on Sustainable Information Engineering and Technology, 2020

Large-Scale Inference of Liver Fat with Neural Networks on UK Biobank Body MRI.

Taro Langner, Robin Strand, Håkan Ahlström, Joel Kullberg

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

2018

Separation of water and fat signal in whole-body gradient echo scans using convolutional neural networks.

Jonathan Andersson, Håkan Ahlström, Joel Kullberg

CoRR, 2018

Fully Convolutional Networks for Automated Segmentation of Abdominal Adipose Tissue Depots in Multicenter Water-Fat MRI.

Taro Langner, Anders Hedström, Håkan Ahlström, Joel Kullberg, Katharina Paulmichl, Daniel Weghuber, Anders Forslund, Peter Bergsten

CoRR, 2018

2015

Automated extraction and labelling of the arterial tree from whole-body MRA data.

Rahil Shahzad, Oleh Dzyubachyk, Marius Staring, Joel Kullberg, Lars Johansson, Håkan Ahlström, Boudewijn P. F. Lelieveldt, Rob J. van der Geest

Medical Image Anal., 2015

2013

Intracranial volume estimated with commonly used methods could introduce bias in studies including brain volume measurements.

Richard Nordenskjöld, Filip Malmberg, Elna-Marie Larsson, Andrew Simmons, Samantha J. Brooks, Lars Lind, Håkan Ahlström, Lars Johansson, Joel Kullberg

NeuroImage, 2013