| 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 | 213 | 2021 |
| 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 | 162 | 2018 |
| 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 | 93 | 2019 |
| 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 | 79 | 2019 |
| Robust abdominal organ segmentation using regional convolutional neural networks M Larsson, Y Zhang, F Kahl Applied Soft Computing 70, 465-471, 2018 | 74 | 2018 |
| Robust abdominal organ segmentation using regional convolutional neural networks M Larsson, Y Zhang, F Kahl Applied Soft Computing 70, 465-471, 2018 | 74 | 2018 |
| 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 | 36* | 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 | 27 | 2021 |
| Deepseg: Abdominal organ segmentation using deep convolutional neural networks M Larsson, Y Zhang, F Kahl Swedish Symposium on Image Analysis 2016, 2016 | 18 | 2016 |
| 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 | 14 | 2022 |
| 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 | 13 | 2022 |
| “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 29 (5), 2531-2539, 2022 | 11 | 2022 |
| 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), 23905, 2021 | 10 | 2021 |
| Brain tumor segmentation using synthetic MR images-A comparison of GANs and diffusion models M Usman Akbar, M Larsson, I Blystad, A Eklund Scientific Data 11 (1), 259, 2024 | 7 | 2024 |
| 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 50 (5), 1510-1520, 2023 | 7 | 2023 |
| 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 | 6 | 2022 |
| 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 | 6 | 2018 |
| 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 | 6 | 2017 |
| 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 | 4 | 2023 |
| 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 | 3 | 2022 |
