output
20182026
most citedFully Convolutional Networks for Automated Segmentation of Abdominal Adipose Tissue Depots in Multicenter Water-Fat MRI

57 citations

5 papers

cs.CV2026

Time-driven Survival Analysis from FDG-PET/CT in Non-Small Cell Lung Cancer

Sambit Tarai, Ashish Chauhan, Elin Lundström +5

Purpose: Automated medical image-based prediction of clinical outcomes, such as overall survival (OS), has great potential in improving patient prognostics and personalized treatme…

cs.CV2025

A method for tissue-mask supported whole-body image registration in the UK Biobank

Yasemin Utkueri, Elin Lundström, Håkan Ahlström +2

The UK Biobank is a large-scale study collecting imaging and non-imaging health data. Robust and accurate inter-subject image registration of these whole-body MR images would enabl…

eess.IV2024

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

Johan Öfverstedt, Elin Lundström, Göran Bergström +2

The study of associations between an individual's age and imaging and non-imaging data is an active research area that attempts to aid understanding of the effects and patterns of…

cs.CV2018★ 49 cited

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

Jonathan Andersson, Håkan Ahlström, Joel Kullberg

Purpose: To perform and evaluate water-fat signal separation of whole-body gradient echo scans using convolutional neural networks. Methods: Whole-body gradient echo scans of 240 s…

cs.CV2018★ 57 cited

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

Taro Langner, Anders Hedström, Katharina Mörwald +5

Purpose: An approach for the automated segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in multicenter water-fat MRI scans of the abdomen was inv…