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Convolutional neural network-based automatic heart segmentation and quantitation in 123I-metaiodobenzylguanidine SPECT imaging

EJNMMI research, 2021-10, Vol.11 (1), p.105-105, Article 105

2021

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

Scientific reports, 2021-12, Vol.11 (1), p.23905-23905, Article 23905

2021

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RECOMIA—a cloud-based platform for artificial intelligence research in nuclear medicine and radiology

EJNMMI physics, 2020-08, Vol.7 (1), p.51-51, Article 51

2020

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Deep learning for segmentation of 49 selected bones in CT scans: First step in automated PET/CT-based 3D quantification of skeletal metastases

European journal of radiology, 2019-04, Vol.113, p.89-95

2019

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Artificial intelligence could alert for focal skeleton/bone marrow uptake in Hodgkin's lymphoma patients staged with FDG-PET/CT

Scientific reports, 2021-05, Vol.11 (1), p.10382-10382, Article 10382

2021

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Shortest Paths with Higher-Order Regularization

IEEE transactions on pattern analysis and machine intelligence, 2015-12, Vol.37 (12), p.2588-2600

2015

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IEEE_Xplore

Deep learning takes the pain out of back breaking work - Automatic vertebral segmentation and attenuation measurement for osteoporosis

Clinical imaging, 2022-01, Vol.81, p.54-59

2022

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Artificial intelligence-aided CT segmentation for body composition analysis: a validation study

European radiology experimental, 2021-03, Vol.5 (1), p.11-11, Article 11

2021

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Improving sensitivity through data augmentation with synthetic lymph node metastases for AI-based analysis of PSMA PET-CT images

Clinical physiology and functional imaging, 2024-04, Vol.In Press

2024

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Shape-aware label fusion for multi-atlas frameworks

Pattern recognition letters, 2019-06, Vol.124, p.109-117

2019

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AI-based detection of lung lesions in [18F]FDG PET-CT from lung cancer patients

EJNMMI physics, 2021-03, Vol.8 (1), p.32-32, Article 32

2021

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Freely available artificial intelligence for pelvic lymph node metastases in PSMA PET-CT that performs on par with nuclear medicine physicians

European journal of nuclear medicine and molecular imaging, 2022, Vol.49 (10), p.3412-3418

2022

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Freely available convolutional neural network-based quantification of PET/CT lesions is associated with survival in patients with lung cancer

EJNMMI physics, 2022-02, Vol.9 (1), p.6-6, Article 6

2022

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Artificial intelligence-based, volumetric assessment of the bone marrow metabolic activity in [ 18 F]FDG PET/CT predicts survival in multiple myeloma

European journal of nuclear medicine and molecular imaging, 2024-03, Vol.In Press

2024

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Application of an artificial intelligence-based tool in [18F]FDG PET/CT for the assessment of bone marrow involvement in multiple myeloma

European journal of nuclear medicine and molecular imaging, 2023-10, Vol.50 (12), p.3697-3708

2023

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Automated artificial intelligence-based analysis of skeletal muscle volume predicts overall survival after cystectomy for urinary bladder cancer

European radiology experimental, 2021-11, Vol.5 (1), p.50-50, Article 50

2021

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Artificial Intelligence Increases the Agreement among Physicians Classifying Focal Skeleton/Bone Marrow Uptake in Hodgkin’s Lymphoma Patients Staged with [18F]FDG PET/CT—a Retrospective Study

Nuclear medicine and molecular imaging, 2023-04, Vol.57 (2), p.110-116

2023

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Freely Available, Fully Automated AI-Based Analysis of Primary Tumour and Metastases of Prostate Cancer in Whole-Body [18F]-PSMA-1007 PET-CT

Diagnostics (Basel), 2022-08, Vol.12 (9), p.2101

2022

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In Defense of 3D-Label Stereo

2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013, p.1730-1737

2013

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Auto-segmentations by convolutional neural network in cervical and anorectal cancer with clinical structure sets as the ground truth

Clinical and translational radiation oncology, 2020-11, Vol.25, p.37-45

2020

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Shortest Paths with Curvature and Torsion

2013 IEEE International Conference on Computer Vision, 2013, p.2024-2031

2013

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An Efficient Optimization Framework for Multi-Region Segmentation Based on Lagrangian Duality

IEEE transactions on medical imaging, 2013-02, Vol.32 (2), p.178-188

2013

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IEEE_Xplore

Deep learning‐based quantification of PET/CT prostate gland uptake: association with overall survival

Clinical physiology and functional imaging, 2020-03, Vol.40 (2), p.106-113

2020

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Partial Enumeration and Curvature Regularization

2013 IEEE International Conference on Computer Vision, 2013, p.2936-2943

2013

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IEEE_Xplore

Automated quantification of reference levels in liver and mediastinal blood pool for the Deauville therapy response classification using FDG‐PET/CT in Hodgkin and non‐Hodgkin lymphomas

Clinical physiology and functional imaging, 2019-01, Vol.39 (1), p.78-84

2019

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Convolutional neural network-based automatic heart segmentation and quantitation in 123I-metaiodobenzylguanidine SPECT imaging

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

RECOMIA—a cloud-based platform for artificial intelligence research in nuclear medicine and radiology

Deep learning for segmentation of 49 selected bones in CT scans: First step in automated PET/CT-based 3D quantification of skeletal metastases

Artificial intelligence could alert for focal skeleton/bone marrow uptake in Hodgkin's lymphoma patients staged with FDG-PET/CT

Shortest Paths with Higher-Order Regularization

Deep learning takes the pain out of back breaking work - Automatic vertebral segmentation and attenuation measurement for osteoporosis

Artificial intelligence-aided CT segmentation for body composition analysis: a validation study

Improving sensitivity through data augmentation with synthetic lymph node metastases for AI-based analysis of PSMA PET-CT images

Shape-aware label fusion for multi-atlas frameworks

AI-based detection of lung lesions in [18F]FDG PET-CT from lung cancer patients

Freely available artificial intelligence for pelvic lymph node metastases in PSMA PET-CT that performs on par with nuclear medicine physicians

Freely available convolutional neural network-based quantification of PET/CT lesions is associated with survival in patients with lung cancer

Artificial intelligence-based, volumetric assessment of the bone marrow metabolic activity in [ 18 F]FDG PET/CT predicts survival in multiple myeloma

Application of an artificial intelligence-based tool in [18F]FDG PET/CT for the assessment of bone marrow involvement in multiple myeloma

Automated artificial intelligence-based analysis of skeletal muscle volume predicts overall survival after cystectomy for urinary bladder cancer

Artificial Intelligence Increases the Agreement among Physicians Classifying Focal Skeleton/Bone Marrow Uptake in Hodgkin’s Lymphoma Patients Staged with [18F]FDG PET/CT—a Retrospective Study

Freely Available, Fully Automated AI-Based Analysis of Primary Tumour and Metastases of Prostate Cancer in Whole-Body [18F]-PSMA-1007 PET-CT

In Defense of 3D-Label Stereo

Auto-segmentations by convolutional neural network in cervical and anorectal cancer with clinical structure sets as the ground truth

Shortest Paths with Curvature and Torsion

An Efficient Optimization Framework for Multi-Region Segmentation Based on Lagrangian Duality

Deep learning‐based quantification of PET/CT prostate gland uptake: association with overall survival

Partial Enumeration and Curvature Regularization

Automated quantification of reference levels in liver and mediastinal blood pool for the Deauville therapy response classification using FDG‐PET/CT in Hodgkin and non‐Hodgkin lymphomas

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