Olof Enqvist

Visar 72 publikationer

2024

Artificial Intelligence-Based Organ Delineation for Radiation Treatment Planning of Prostate Cancer on Computed Tomography

Eirini Polymeri, Åse A. Johnsson, Olof Enqvist et al
Advances in Radiation Oncology. Vol. 9 (3)
Artikel i vetenskaplig tidskrift
2024

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

Christos Sachpekidis, Olof Enqvist, Johannes Ulén et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 51 (8), p. 2293-2307
Artikel i vetenskaplig tidskrift
2024

Applications of Artificial Intelligence in PSMA PET/CT for Prostate Cancer Imaging

S. L. Belal, Sophia Frantz, David Minarik et al
Seminars in Nuclear Medicine. Vol. 54 (1), p. 141-149
Reviewartikel
2024

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

E. Tragardh, Johannes Ulén, Olof Enqvist et al
Clinical Physiology and Functional Imaging. Vol. 44 (4), p. 332-339
Artikel i vetenskaplig tidskrift
2024

A novel model of artificial intelligence based automated image analysis of CT urography to identify bladder cancer in patients investigated for macroscopic hematuria

Suleiman Abuhasanein, L. Edenbrandt, Olof Enqvist et al
Scandinavian Journal of Urology. Vol. 59, p. 90-97
Artikel i vetenskaplig tidskrift
2023

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

Christos Sachpekidis, Olof Enqvist, Johannes Ulén et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 50 (12), p. 3697-3708
Artikel i vetenskaplig tidskrift
2023

Increased sensitivity for AI-based detection of lymph node metastases on [18F]-PSMA-1007 PET-CT when adding synthetic data to the training data

E. Tragardh, J. Ulen, Olof Enqvist et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 50 (SUPPL 1), p. S321-S321
Övrigt konferensbidrag
2023

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

C. Sachpekidis, Olof Enqvist, J. Ulen et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 50 (SUPPL 1), p. S409-S410
Övrigt konferensbidrag
2023

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

May Sadik, Jesus Lopez-Urdaneta, Johannes Ulen et al
Nuclear Medicine and Molecular Imaging. Vol. 57 (2), p. 110-116
Artikel i vetenskaplig tidskrift
2023

Common carotid segmentation in <sup>18</sup>F-sodium fluoride PET/CT scans: Head-to-head comparison of artificial intelligence-based and manual method

Reza Piri, Yaran Hamakan, Ask Vang et al
Clinical Physiology and Functional Imaging. Vol. 43 (2), p. 71-77
Artikel i vetenskaplig tidskrift
2023

AI-based quantification of whole-body tumour burden on somatostatin receptor PET/CT

Anni Gålne, Olof Enqvist, Anna Sundlöv et al
European Journal of Hybrid Imaging. Vol. 7 (1)
Artikel i vetenskaplig tidskrift
2023

Convolutional neural network-based left ventricle segmentations in 123I-MIBG SPECT-CT images

Shintaro Saito, Kenichi Nakajima, Lars Edenbrandt et al
Journal of Nuclear Medicine. Vol. 64
Övrigt konferensbidrag
2022

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

Elin Tragardh, Olof Enqvist, Johannes Ulen et al
Diagnostics. Vol. 12 (9)
Artikel i vetenskaplig tidskrift
2022

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

E. Tragardh, Olof Enqvist, Johannes Ulén et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 49 (10), p. 3412-3418
Artikel i vetenskaplig tidskrift
2022

AI-based detection and characterization of lung tumors in 18F-FDG-PET/CT including measurements of tumor dimension in CT

P. Borrelli, Måns Larsson, R. Rossi Norrlund et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 49 (Suppl 1), p. S620-S620
Övrig text i vetenskaplig tidskrift
2022

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

Reza Piri, L. Edenbrandt, Måns Larsson et al
Journal of Nuclear Cardiology. Vol. 29 (5), p. 2531-2539
Artikel i vetenskaplig tidskrift
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. 42 (4), p. 225-232
Artikel i vetenskaplig tidskrift
2022

Aortic wall segmentation in F-18-sodium fluoride PET/CT scans: Head-to-head comparison of artificial intelligence-based versus manual segmentation

Reza Piri, Lars Edenbrandt, Mans Larsson et al
Journal of Nuclear Cardiology. Vol. 29 (4), p. 2001-2010
Artikel i vetenskaplig tidskrift
2022

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

Pablo Borrelli, Jose Luis Loaiza Gongora, Reza Kaboteh et al
EJNMMI Physics. Vol. 9 (1)
Artikel i vetenskaplig tidskrift
2022

Artificial intelligence for the detection of primary tumour, recurrence and metastases in PSMA PET-CT in prostate cancer

E. Tragardh, Olof Enqvist, J. Ulen et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 49 (Suppl 1), p. S270-S270
Övrig text i vetenskaplig tidskrift
2021

Convolutional neural network-based automatic calculation of heart counts in123I-MIBG SPECT imaging

Shintaro Saito, Kenichi Nakajima, Lars Edenbrandt et al
Journal of Nuclear Medicine. Vol. 62
Övrigt konferensbidrag
2021

Fast, automated artificial intelligence-based aorta segmentation in 18F-sodium fluoride PET/CT scans: head-to-head comparison with manual segmentation

Reza Piri, Lars Edenbrandt, Mans Larsson et al
Journal of Nuclear Medicine. Vol. 62
Övrigt konferensbidrag
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

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

Shintaro Saito, Kenichi Nakajima, L. Edenbrandt et al
EJNMMI Research. Vol. 11 (1)
Artikel i vetenskaplig tidskrift
2021

AI-based quantification of PET/CT lesions is associated with survival in lung cancer patients

Pablo Borrelli, Jose Luis Loaiza Gongora, Reza Kaboteh et al
Journal of Nuclear Medicine. Vol. 62
Övrigt konferensbidrag
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
2021

PET/CT in localizing inflammation and microcalcification as potential causes of ongoing low back pain

Amalie Horstmann Noddeskou-Fink, Reza Piri, Oke Gerke et al
Journal of Nuclear Medicine. Vol. 62
Övrigt konferensbidrag
2021

Artificial intelligence-based measurements of PET/CT imaging biomarkers are associated with disease-specific survival of high-risk prostate cancer patients

Eirini Polymeri, Henrik Kjölhede, Olof Enqvist et al
Scandinavian Journal of Urology. Vol. 55 (6), p. 427-433
Artikel i vetenskaplig tidskrift
2021

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

Pablo Borrelli, John Ly, R. Kaboteh et al
EJNMMI Physics. Vol. 8 (1)
Artikel i vetenskaplig tidskrift
2021

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

Thomas Ying, Pablo Borrelli, L. Edenbrandt et al
European Radiology Experimental. Vol. 5 (1)
Artikel i vetenskaplig tidskrift
2021

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

M. Sadik, Jesús López-Urdaneta, Johannes Ulén et al
Scientific Reports. Vol. 11 (1)
Artikel i vetenskaplig tidskrift
2021

AI tool decreases inter-observer variability in the analysis of PSMA-PET/CT

Pablo Borrelli, Johannes Ulen, Olof Enqvist et al
Journal of Nuclear Medicine. Vol. 62
Övrigt konferensbidrag
2021

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

Pablo Borrelli, R. Kaboteh, Olof Enqvist et al
European Radiology Experimental. Vol. 5 (1)
Artikel i vetenskaplig tidskrift
2020

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

E. Tragardh, Pablo Borrelli, R. Kaboteh et al
EJNMMI Physics. Vol. 7 (1)
Artikel i vetenskaplig tidskrift
2020

Application of convolutional neural network to(123)I-MIBG SPECT imaging: automatic quantitation vs. manual measurements

Shintaro Saito, Kenichi Nakajima, Lars Edenbrandt et al
Övrigt konferensbidrag
2020

Denoising of Scintillation Camera Images Using a Deep Convolutional Neural Network: A Monte Carlo Simulation Approach

David Minarik, Olof Enqvist, E. Tragardh
Journal of Nuclear Medicine. Vol. 61 (2), p. 298-303
Artikel i vetenskaplig tidskrift
2020

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

Eirini Polymeri, M. Sadik, R. Kaboteh et al
Clinical Physiology and Functional Imaging. Vol. 40 (2), p. 106-113
Artikel i vetenskaplig tidskrift
2019

AI-based Tools for Automated Quantification of PET/CT Studies

L. Edenbrandt, J. Ulen, Olof Enqvist et al
Övrigt konferensbidrag
2019

AI-based Detection of Lung Lesions in FDG-PET/CT from Lung Cancer Patients

L. Edenbrandt, R. Kaboteh, S. Salehian et al
Övrigt konferensbidrag
2019

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

May Sadik, Erica Lind, Eirini Polymeri et al
Clinical Physiology and Functional Imaging. Vol. 39 (1), p. 78-84
Artikel i vetenskaplig tidskrift
2019

Shape-aware label fusion for multi-atlas frameworks

Jennifer Alvén, Fredrik Kahl, Olof Enqvist
Pattern Recognition Letters. Vol. 124, p. 109-117
Artikel i vetenskaplig tidskrift
2019

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

S. L. Belal, M. Sadik, R. Kaboteh et al
European Journal of Radiology. Vol. 113, p. 89-95
Artikel i vetenskaplig tidskrift
2019

Artificial intelligence-based versus manual assessment of prostate cancer in the prostate gland: a method comparison study

Mike A. Mortensen, Pablo Borrelli, M. H. Poulsen et al
Clinical Physiology and Functional Imaging. Vol. 39 (6), p. 399-406
Artikel i vetenskaplig tidskrift
2018

Artificial Intelligence Based Method for Automated PET/CT Measurements of Prostate Gland Volume and Choline Uptake

Pablo Borrelli, Mike Mortensen, Olof Enqvist et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 45 (Supplement: 1 ), p. S531-S532
Övrigt konferensbidrag
2018

Deep learning algorithms for automated assessment of total and cancerous prostate gland volume based on PET/CT

Pablo Borrelli, Mike Mortensen, Olof Enqvist et al
Journal of Nuclear Medicine. Vol. 59 (Supplement 1)
Paper i proceeding
2017

Automated 3D segmentation of the prostate gland in CT images - a first step towards objective measurements of prostate uptake in PET and SPECT images

May Sadik, Eirini Polymeri, Reza Kaboteh et al
Journal of Nuclear Medicine. Vol. 58 (supplement 1)
Artikel i vetenskaplig tidskrift
2017

Multiatlas Segmentation Using Robust Feature-Based Registration

Frida Fejne, Matilda Landgren, Jennifer Alvén et al
, Cloud-Based Benchmarking of Medical Image Analysis, p. 203-218
Kapitel i bok
2017

Action sequencing in the spontaneous swimming behavior of zebrafish larvae - implications for drug development

T. Palmer, F. Ek, Olof Enqvist et al
Scientific Reports. Vol. 7 (1), p. Article Number: 3191-
Artikel i vetenskaplig tidskrift
2017

3D prostate gland uptake of 18F-choline - association with overall survival in patients with hormone-naïve prostate cancer

May Sadik, Eirini Polymeri, Reza Kaboteh et al
Journal of Nuclear Medicine. Vol. 58 (supplement 1), p. 544-
Artikel i vetenskaplig tidskrift
2017

Analytical validation of an automated method for segmentation of the prostate gland in CT images

May Sadik, Eirini Polymeri, Reza Kaboteh et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 44 (supplement issue 2)
Artikel i vetenskaplig tidskrift
2017

Convolutional neural networks for segmentation of 49 selected bones in CT images show high reproducibility

May Sadik, Reza Kaboteh, Elin Trägårdh et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 44 (Supplement 2)
Artikel i vetenskaplig tidskrift
2017

Automated evaluation of normal uptake in different skeletal parts using 18F-sodium fluoride (NaF) PET/CT using a new convolutional neural network method

May Sadik, Sarah Lindgren Belal, Reza Kaboteh et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 44 (Supplement 2)
Artikel i vetenskaplig tidskrift
2017

3D skeletal uptake of F-18 sodium fluoride in PET/CT images is associated with overall survival in patients with prostate cancer

S. L. Belal, M. Sadik, R. Kaboteh et al
EJNMMI Research. Vol. 7 (1)
Artikel i vetenskaplig tidskrift
2017

Automated quantification of reference levels in liver and mediastinum (blood pool) for the Deauville therapy response classification using FDG-PET/CT in lymphoma patients

Erica Lind, May Sadik, Olof Enqvist et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 44 (supplement 2)
Artikel i vetenskaplig tidskrift
2017

Convolutional neural network based quantification of choline uptake in PET/CT studies is associated with overall survival in patients with prostate cancer

Reza Kaboteh, Eirini Polymeri, May Sadik et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 44 (supplement 2)
Artikel i vetenskaplig tidskrift
2017

Variability in reference levels for Deauville classifications applied to lymphoma patients examined with 18F-FDG-PET/CT

May Sadik, Erica Lind, Olof Enqvist et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 44
Artikel i vetenskaplig tidskrift
2017

City-scale localization for cameras with known vertical direction

Linus Svärm, Olof Enqvist, Fredrik Kahl et al
IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 39 (7), p. 1455-1461
Artikel i vetenskaplig tidskrift
2016

Automatic pericardium segmentation and quantification of epicardial fat from computed tomography angiography

Alexander Norlén, Jennifer Alvén, David Molnar et al
Journal of Medical Imaging. Vol. 3 (3), p. Article number 034003-
Artikel i vetenskaplig tidskrift
2016

Efficient algorithms for robust estimation of relative translation

Johan Fredriksson, Viktor Larsson, Carl Olsson et al
Image and Vision Computing. Vol. 52, p. 114-124
Artikel i vetenskaplig tidskrift
2016

Automated segmentation of the skeleton in PET/CT scans

May Sadik, Reza Kaboteh, N. Hasani et al
European Journal of Nuclear Medicine and Molecular Imaging. Vol. 43, p. S392-S392
Övrigt konferensbidrag
2016

Überatlas: Fast and robust registration for multi-atlas segmentation

Jennifer Alvén, Alexander Norlén, Olof Enqvist et al
Pattern Recognition Letters. Vol. 80, p. 249-255
Artikel i vetenskaplig tidskrift
2015

Good Features for Reliable Registration in Multi-Atlas Segmentation

Fredrik Kahl, Jennifer Alvén, Olof Enqvist et al
CEUR Workshop Proceedings. Vol. 1390 (January), p. 12-17
Paper i proceeding
2015

Tractable Algorithms for Robust Model Estimation

Olof Enqvist, Erik Ask, Fredrik Kahl et al
International Journal of Computer Vision. Vol. 112 (1), p. 115-129
Artikel i vetenskaplig tidskrift
2015

Improving Robustness for Inter-Subject Medical Image Registration Using a Feature-Based Approach

Linus Svärm, Olof Enqvist, Fredrik Kahl et al
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015, Brooklyn, United States, 16-19 April 2015. Vol. 2015-July, p. 824-828
Paper i proceeding
2015

Überatlas: Robust Speed-Up of Feature-Based Registration and Multi-Atlas Segmentation

Jennifer Alvén, Alexander Norlén, Olof Enqvist et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9127, p. 92-102
Paper i proceeding
2015

A Combinatorial Approach to L1-Matrix Factorization

Fangyuan Jiang, Olof Enqvist, Fredrik Kahl
Journal of Mathematical Imaging and Vision. Vol. 51 (3), p. 430-441
Artikel i vetenskaplig tidskrift
2014

Accurate Localization and Pose Estimation for Large 3D Models

Linus Svärm, Olof Enqvist, Magnus Oskarsson et al
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, p. 532-539
Paper i proceeding
2014

Tractable and Reliable Registration of 2D Point Sets

Erik Ask, Olof Enqvist, Linus Svärm et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8689 LNCS (PART 1), p. 393-406
Paper i proceeding
2014

Fast and Reliable Two-View Translation Estimation

Johan Fredriksson, Olof Enqvist, Fredrik Kahl
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, p. 1606-1612
Paper i proceeding

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