Search Results - "Larsson, Måns"
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Robust abdominal organ segmentation using regional convolutional neural networks
Published in Applied soft computing (01-09-2018)“…[Display omitted] •A fully automatic system for abdominal organ segmentation is presented.•Regional convolutional neural networks are used for organwise…”
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Deep learning analysis of serial digital breast tomosynthesis images in a prospective cohort of breast cancer patients who received neoadjuvant chemotherapy
Published in European journal of radiology (01-09-2024)“…•Novel study to apply AI to breast tomosynthesis for treatment response prediction.•AI model shows high discriminative performance (AUC 0.83) for response…”
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Artificial intelligence based automatic quantification of epicardial adipose tissue suitable for large scale population studies
Published in Scientific reports (13-12-2021)“…To develop a fully automatic model capable of reliably quantifying epicardial adipose tissue (EAT) volumes and attenuation in large scale population studies to…”
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Brain tumor segmentation using synthetic MR images - A comparison of GANs and diffusion models
Published in Scientific data (29-02-2024)“…Large annotated datasets are required for training deep learning models, but in medical imaging data sharing is often complicated due to ethics, anonymization…”
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Improving sensitivity through data augmentation with synthetic lymph node metastases for AI‐based analysis of PSMA PET‐CT images
Published in Clinical physiology and functional imaging (01-07-2024)“…Background We developed a fully automated artificial intelligence (AI)AI‐based‐based method for detecting suspected lymph node metastases in prostate‐specific…”
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Pre-diabetes is associated with attenuation rather than volume of epicardial adipose tissue on computed tomography
Published in Scientific reports (28-01-2023)“…The volume of epicardial adipose tissue (EATV) is increased in type-2 diabetes (T2D), while its attenuation (EATA) appears to be decreased. Similar patterns…”
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NoiseNet, a fully automatic noise assessment tool that can identify non-diagnostic CCTA examinations
Published in The international journal of cardiovascular imaging (01-07-2024)“…Image noise and vascular attenuation are important factors affecting image quality and diagnostic accuracy of coronary computed tomography angiography (CCTA)…”
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“Global” cardiac atherosclerotic burden assessed by artificial intelligence-based versus manual segmentation in 18F-sodium fluoride PET/CT scans: Head-to-head comparison
Published in Journal of nuclear cardiology (01-10-2022)“…Artificial intelligence (AI) is known to provide effective means to accelerate and facilitate clinical and research processes. So in this study it was aimed to…”
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Alluvial aquifer thickness and bedrock structure delineation by electromagnetic methods in the highlands of Bolivia
Published in Environmental earth sciences (01-02-2019)“…The porous aquifers in the area called Challapampa are the most important groundwater reservoirs that supply drinking water to Oruro city in the highlands of…”
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Manual prostate MRI segmentation by readers with different experience: a study of the learning progress
Published in European radiology (2024)“…Objective To evaluate the learning progress of less experienced readers in prostate MRI segmentation. Materials and methods One hundred bi-parametric prostate…”
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Automated quantification of PET/CT skeletal tumor burden in prostate cancer using artificial intelligence: The PET index
Published in European journal of nuclear medicine and molecular imaging (2023)“…Purpose Consistent assessment of bone metastases is crucial for patient management and clinical trials in prostate cancer (PCa). We aimed to develop a fully…”
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Common carotid segmentation in 18F‐sodium fluoride PET/CT scans: Head‐to‐head comparison of artificial intelligence‐based and manual method
Published in Clinical physiology and functional imaging (01-03-2023)“…Background Carotid atherosclerosis is a major cause of stroke, traditionally diagnosed late. Positron emission tomography/computed tomography (PET/CT) with…”
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Artificial intelligence‐based detection of lymph node metastases by PET/CT predicts prostate cancer‐specific survival
Published in Clinical physiology and functional imaging (01-01-2021)“…Introduction Lymph node metastases are a key prognostic factor in prostate cancer (PCa), but detecting lymph node lesions from PET/CT images is a subjective…”
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Pneumococcal carriage among children aged 4 – 12 years in Angola 4 years after the introduction of a pneumococcal conjugate vaccine
Published in Vaccine (25-11-2020)“…Children in Angola are affected by a high burden of disease caused by pneumococcal infections. The 13-valent pneumococcal conjugate vaccine (PCV13) was…”
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Aortic wall segmentation in 18F-sodium fluoride PET/CT scans: Head-to-head comparison of artificial intelligence-based versus manual segmentation
Published in Journal of nuclear cardiology (01-08-2022)“…We aimed to establish and test an automated AI-based method for rapid segmentation of the aortic wall in positron emission tomography/computed tomography…”
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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
Published in Clinical physiology and functional imaging (01-07-2022)“…Background Current imaging modalities are often incapable of identifying nociceptive sources of low back pain (LBP). We aimed to characterize these by means of…”
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Back to the Feature: Learning Robust Camera Localization from Pixels to Pose
Published in 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (01-01-2021)“…Camera pose estimation in known scenes is a 3D geometry task recently tackled by multiple learning algorithms. Many regress precise geometric quantities, like…”
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Conference Proceeding -
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A Cross-Season Correspondence Dataset for Robust Semantic Segmentation
Published in 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (01-06-2019)“…In this paper, we present a method to utilize 2D-2D point matches between images taken during different image conditions to train a convolutional neural…”
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Conference Proceeding -
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Fine-Grained Segmentation Networks: Self-Supervised Segmentation for Improved Long-Term Visual Localization
Published in 2019 IEEE/CVF International Conference on Computer Vision (ICCV) (01-10-2019)“…Long-term visual localization is the problem of estimating the camera pose of a given query image in a scene whose appearance changes over time. It is an…”
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