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Måns Larsson
Måns Larsson
Eigenvision AB
Verified email at chalmers.se - Homepage
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Year
Back to the Feature: Learning Robust Camera Localization from Pixels to Pose
PE Sarlin, A Unagar, M Larsson, H Germain, C Toft, V Larsson, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
1982021
Conditional random fields meet deep neural networks for semantic segmentation: Combining probabilistic graphical models with deep learning for structured prediction
A Arnab, S Zheng, S Jayasumana, B Romera-Paredes, M Larsson, ...
IEEE Signal Processing Magazine 35 (1), 37-52, 2018
1612018
A cross-season correspondence dataset for robust semantic segmentation
M Larsson, E Stenborg, L Hammarstrand, M Pollefeys, T Sattler, F Kahl
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
912019
Fine-grained segmentation networks: Self-supervised segmentation for improved long-term visual localization
M Larsson, E Stenborg, C Toft, L Hammarstrand, T Sattler, F Kahl
Proceedings of the IEEE/CVF International Conference on Computer Vision, 31-41, 2019
772019
Robust abdominal organ segmentation using regional convolutional neural networks
M Larsson, Y Zhang, F Kahl
Applied Soft Computing 70, 465-471, 2018
722018
Robust abdominal organ segmentation using regional convolutional neural networks
M Larsson, Y Zhang, F Kahl
Applied Soft Computing 70, 465-471, 2018
722018
A projected gradient descent method for crf inference allowing end-to-end training of arbitrary pairwise potentials
M Larsson, A Arnab, F Kahl, S Zheng, P Torr
Energy Minimization Methods in Computer Vision and Pattern Recognition: 11th …, 2018
35*2018
Artificial intelligence‐based detection of lymph node metastases by PET/CT predicts prostate cancer‐specific survival
P Borrelli, M Larsson, J Ulén, O Enqvist, E Trägårdh, MH Poulsen, ...
Clinical Physiology and Functional Imaging 41 (1), 62-67, 2021
242021
Deepseg: Abdominal organ segmentation using deep convolutional neural networks
M Larsson, Y Zhang, F Kahl
Swedish Symposium on Image Analysis 2016, 2016
172016
Aortic wall segmentation in 18F-sodium fluoride PET/CT scans: Head-to-head comparison of artificial intelligence-based versus manual segmentation
R Piri, L Edenbrandt, M Larsson, O Enqvist, AH Nøddeskou-Fink, O Gerke, ...
Journal of Nuclear Cardiology 29 (4), 2001-2010, 2022
132022
Analysis of mammograms using artificial intelligence to predict response to neoadjuvant chemotherapy in breast cancer patients: proof of concept
I Skarping, M Larsson, D Förnvik
European Radiology, 1-11, 2022
132022
Artificial intelligence based automatic quantification of epicardial adipose tissue suitable for large scale population studies
D Molnar, O Enqvist, J Ulén, M Larsson, J Brandberg, ÅA Johnsson, ...
Scientific Reports 11 (1), 1-13, 2021
102021
“Global” cardiac atherosclerotic burden assessed by artificial intelligence-based versus manual segmentation in 18F-sodium fluoride PET/CT scans: Head-to-head comparison
R Piri, L Edenbrandt, M Larsson, O Enqvist, S Skovrup, KK Iversen, ...
Journal of Nuclear Cardiology, 1-9, 2021
92021
Automated quantification of PET/CT skeletal tumor burden in prostate cancer using artificial intelligence: The PET index
S Lindgren Belal, M Larsson, J Holm, KM Buch-Olsen, J Sörensen, ...
European Journal of Nuclear Medicine and Molecular Imaging, 1-11, 2023
62023
PET/CT imaging of spinal inflammation and microcalcification in patients with low back pain: A pilot study on the quantification by artificial intelligence‐based segmentation
R Piri, AH Nøddeskou‐Fink, O Gerke, M Larsson, L Edenbrandt, O Enqvist, ...
Clinical Physiology and Functional Imaging 42 (4), 225-232, 2022
62022
Revisiting Deep Structured Models for Pixel-Level Labeling with Gradient-Based Inference
M Larsson, A Arnab, S Zheng, P Torr, F Kahl
SIAM Journal on Imaging Sciences 11 (4), 2610-2628, 2018
62018
Max-margin learning of deep structured models for semantic segmentation
M Larsson, J Alvén, F Kahl
Image Analysis: 20th Scandinavian Conference, SCIA 2017, Tromsø, Norway …, 2017
62017
Pre-diabetes is associated with attenuation rather than volume of epicardial adipose tissue on computed tomography
D Molnar, E Björnson, M Larsson, M Adiels, A Gummesson, F Bäckhed, ...
Scientific Reports 13 (1), 1623, 2023
32023
Does an ensemble of GANs lead to better performance when training segmentation networks with synthetic images?
M Larsson, MU Akbar, A Eklund
arXiv preprint arXiv:2211.04086, 2022
32022
Common carotid segmentation in 18F‐sodium fluoride PET/CT scans: Head‐to‐head comparison of artificial intelligence‐based and manual method
R Piri, Y Hamakan, A Vang, L Edenbrandt, M Larsson, O Enqvist, O Gerke, ...
Clinical Physiology and Functional Imaging 43 (2), 71-77, 2023
22023
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