Måns Larsson

Visar 15 publikationer

2022

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

Reza Piri, Amalie H. Nøddeskou-Fink, Oke Gerke et al
Clinical Physiology and Functional Imaging. Vol. In Press
Artikel i vetenskaplig tidskrift
2021

Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survival

Pablo Borrelli, Måns Larsson, Johannes Ulen et al
Clinical Physiology and Functional Imaging. Vol. 41 (1), p. 62-67
Artikel i vetenskaplig tidskrift
2021

“Global” cardiac atherosclerotic burden assessed by artificial intelligence-based versus manual segmentation in 18F-sodium fluoride PET/CT scans: Head-to-head comparison

Reza Piri, L. Edenbrandt, Måns Larsson et al
Journal of Nuclear Cardiology. Vol. In Press
Artikel i vetenskaplig tidskrift
2021

Artificial intelligence based automatic quantification of epicardial adipose tissue suitable for large scale population studies

David Molnar, Olof Enqvist, Johannes Ulén et al
Scientific Reports. Vol. 11 (1)
Artikel i vetenskaplig tidskrift
2019

Fine-Grained Segmentation Networks: Self-Supervised Segmentation for Improved Long-Term Visual Localization

Måns Larsson, Erik Stenborg, Carl Toft et al
Proceedings of the IEEE International Conference on Computer Vision (October), p. 31-41
Paper i proceeding
2019

A cross-season correspondence dataset for robust semantic segmentation

Måns Larsson, Erik Stenborg, Lars Hammarstrand et al
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol. 2019-June, p. 9524-9534
Paper i proceeding
2018

A projected gradient descent method for crf inference allowing end-to-end training of arbitrary pairwise potentials

Måns Larsson, Anurag Arnab, Fredrik Kahl et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 10746, p. 564-579
Paper i proceeding
2018

Robust Abdominal Organ Segmentation Using Regional Convolutional Neural Networks

Måns Larsson, Zhang Yuhang, Fredrik Kahl
Applied Soft Computing Journal. Vol. 70, p. 465-470
Artikel i vetenskaplig tidskrift
2018

Revisiting Deep Structured Models for Pixel-Level Labeling with Gradient-Based Inference

Måns Larsson, Anurag Arnab, Shuai Zheng et al
SIAM Journal on Imaging Sciences. Vol. 11 (4), p. 2610-2628
Artikel i vetenskaplig tidskrift
2018

Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction

Anurag Arnab, Shuai Zheng, Sadeep Jayasumana et al
IEEE Signal Processing Magazine. Vol. 35 (1), p. 37-52
Artikel i vetenskaplig tidskrift
2017

Max-margin learning of deep structured models for semantic segmentation

Måns Larsson, Jennifer Alvén, Fredrik Kahl
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 10270 LNCS, p. 28-40
Paper i proceeding
2017

Robust abdominal organ segmentation using regional convolutional neural networks

Måns Larsson, Zhang Yuhang, Fredrik Kahl
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 10270 LNCS, p. 41-52
Paper i proceeding
2016

Deepseg: Abdominal Organ Segmentation Using Deep Convolutional Neural Networks

Måns Larsson, Yuhang Zhang, Fredrik Kahl
SSBA
Övrigt konferensbidrag

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