Category: Radiology

Research

Computed tomography | Echocardiography | ECG | Magnetic resonance imaging | Cardiology | Radiology
Cardiovascular Lab
Developing and bringing AI solutions to cardiovascular disease care.

Magnetic resonance imaging | Abdomen | Intestines | Radiology
Gastrointestinal Lab
Developing and bringing AI solutions to subjects with gastrointestinal disorders or diseases.

Projects

2021
 | 
2026
Echocardiography | ECG | Magnetic resonance imaging | AI for Cardiology | Cardiology | Radiology | MRI | CT
Identification of deterioration in non-hospitalized heart failure patients
Developing AI-based decision-making using multi-modal data to stratify hospitalization risk in heart failure
ONGOING

2011
 | 
2013
Computed tomography | Cardiovascular | Radiology
Atherosclerotic calcifications of head and neck arteries
Relating calcifications and stenosis in the internal carotid artery in patients with symptoms of cerebrovascular disease
FINISHED

2016
 | 
2020
Magnetic resonance imaging | Neonatology | Radiology
Quantitative analysis of nutrition supplements on neonatal brain development
Developing AI methods for quantitative description of neonatal brain development with MRI
FINISHED

2012
 | 
2016
Magnetic resonance imaging | Neonatology | Radiology
Automatic analysis of the developing neonatal brain
Developing AI methods for automatic and quantitative analysis of neonatal brain with MRI.
FINISHED

2012
 | 
2016
Computed tomography | Radiology
Identification and quantification of arterial calcifications in cardiac CT
Developing machine learning algorithms for coronary calcium scoring in cardiac CT
FINISHED

2014
 | 
2018
Computed tomography | Cardiovascular | Radiology
Automatic detection of CVD and osteoporosis in lung cancer screening trials
Developing AI methods for automatic detection of cardiovascular and spine diseases in chest CT
FINISHED

2012
 | 
2017
Computed tomography | Cardiovascular | Genetics | Radiology
Cardiovascular phenotype-genotype analysis within a CT based lung cancer screening trial
Developing machine learning methods to measure existing and novel imaging biomarkers related to cardiovascular disease in chest CT
FINISHED

2015
 | 
2019
Computed tomography | Cardiovascular | Cardiology | Radiology
Automatic identification of patients with functionally significant obstructive coronary artery disease using non-invasive cardiac CT
Developing AI models to identify patients with functionally significant coronary artery disease.
FINISHED

2019
 | 
2024
Magnetic resonance imaging | Abdomen | Intestines | Radiology
AI for the detection of gastrointestinal motility in 3D cine MR
Develop a deep learning method to automatically quantify gastrointestinal motion using dynamic 2D and 3D MRI of the abdomen.
FINISHED

2020
 | 
2024
Computed tomography | AI for Cardiology | Cardiovascular | Cardiology | Radiology
Non-invasive and intravascular identification and drug-eluting balloon treatment of vulnerable lipid-rich plaques
Developing non-invasive AI-based method that detects and characterizes lipid-rich plaque in computed tomography coronary angiography.
ONGOING

2017
 | 
2022
Magnetic resonance imaging | AI for Cardiology | Cardiology | Radiology
DLMedIA: Dynamic deep learning in cardiac disease
Developing dynamic learning strategies for deep learning systems in clinical environments.
FINISHED

2017
 | 
2022
Computed tomography | AI for Cardiology | Cardiovascular | Cardiology | Radiology
DLMedIA: Deep transfer learning in cardiovascular disease
Developing deep transfer learning techniques to effectively analyze medical imaging data with variation in scanners, scan protocols, and patient populations.
FINISHED

2017
 | 
2022
Computed tomography | Cardiovascular | Cardiology | Radiology
DLMedIA: Deep generative models for cardiovascular disease
Developing deep generative models to learn more efficiently from less data in the analysis of cardiac CT.
FINISHED

2017
 | 
2022
Computed tomography | Magnetic resonance imaging | Cardiovascular | Cardiology | Radiology
DLMedIA: High dimensional data for cardiovascular disease
Developing deep learning techniques for quantitative analysis of 4- and 5-dimensional CT and MR images of the heart
FINISHED

2019
 | 
2023
Computed tomography | Cardiovascular | Cardiology | Radiology
AI for CCTA-based prediction of FFR
Developing AI models to predict invasively measured fractional flow reserve noninvasively
FINISHED