Olof Enqvist

2024

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

2024

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

2024

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

2024

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

2023

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

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

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

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

2023

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

2023

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

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

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

2022

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

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

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

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

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

2022

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

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

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

Global cardiac atherosclerotic burden assessed by fast automated artificial intelligence-based heart segmentation in F-18-sodium fluoride PET/CT scans: head-to-head comparison with manual segmentation

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

2021

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

2021

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

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

2021

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

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

2021

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

2021

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

2021

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

2021

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

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

2021

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

2020

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

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

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

2020

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

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

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

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

Artificial intelligence can discriminate between focal and normal bone/bone marrow uptake in lymphoma patients staged with FDG-PET/CT- a descriptive study

Shape-aware label fusion for multi-atlas frameworks

2019

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

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

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

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

Multiatlas Segmentation Using Robust Feature-Based Registration

2017

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

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

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

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

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

2017

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

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

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

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

City-scale localization for cameras with known vertical direction

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

Efficient algorithms for robust estimation of relative translation

Automated segmentation of the skeleton in PET/CT scans

Überatlas: Fast and robust registration for multi-atlas segmentation

Good Features for Reliable Registration in Multi-Atlas Segmentation

Tractable Algorithms for Robust Model Estimation

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

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

A Combinatorial Approach to L1-Matrix Factorization

2014

Accurate Localization and Pose Estimation for Large 3D Models

Tractable and Reliable Registration of 2D Point Sets

Fast and Reliable Two-View Translation Estimation