Håkan Ahlström

Orcid: 0000-0002-8701-969X

According to our database1, Håkan Ahlström authored at least 18 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
A method for supervoxel-wise association studies of age and other non-imaging variables from coronary computed tomography angiograms.
CoRR, 2024

Prediction of Total Metabolic Tumor Volume from Tissue-Wise FDG-PET/CT Projections, Interpreted Using Cohort Saliency Analysis.
Proceedings of the Medical Image Understanding and Analysis - 28th Annual Conference, 2024

2023
Automatic segmentation of large-scale CT image datasets for detailed body composition analysis.
BMC Bioinform., December, 2023

Leveraging point annotations in segmentation learning with boundary loss.
CoRR, 2023

Introducing Spatial Context in Patch-Based Deep Learning for Semantic Segmentation in Whole Body MRI.
Proceedings of the Image Analysis - 22nd Scandinavian Conference, 2023

2021
MIMIR: Deep Regression for Automated Analysis of UK Biobank Body MRI.
CoRR, 2021

Deep regression for uncertainty-aware and interpretable analysis of large-scale body MRI.
CoRR, 2021

Uncertainty-aware body composition analysis with deep regression ensembles on UK Biobank MRI.
Comput. Medical Imaging Graph., 2021

2020
Identifying Morphological Indicators of Aging With Neural Networks on Large-Scale Whole-Body MRI.
IEEE Trans. Medical Imaging, 2020

Kidney segmentation in neck-to-knee body MRI of 40, 000 UK Biobank participants.
CoRR, 2020

Large-scale biometry with interpretable neural network regression on UK Biobank body MRI.
CoRR, 2020

Fast graph-cut based optimization for practical dense deformable registration of volume images.
Comput. Medical Imaging Graph., 2020

Recent advances in large scale whole body MRI image analysis: Imiomics.
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.
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.
CoRR, 2018

Fully Convolutional Networks for Automated Segmentation of Abdominal Adipose Tissue Depots in Multicenter Water-Fat MRI.
CoRR, 2018

2015
Automated extraction and labelling of the arterial tree from whole-body MRA data.
Medical Image Anal., 2015

2013
Intracranial volume estimated with commonly used methods could introduce bias in studies including brain volume measurements.
NeuroImage, 2013


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