Detalhe da pesquisa
1.
Localization of contrast-enhanced breast lesions in ultrafast screening MRI using deep convolutional neural networks.
Eur Radiol
; 34(3): 2084-2092, 2024 Mar.
Artigo
em Inglês
| MEDLINE | ID: mdl-37658141
2.
Performance of Lung-RADS in different target populations: a systematic review and meta-analysis.
Eur Radiol
; 34(3): 1877-1892, 2024 Mar.
Artigo
em Inglês
| MEDLINE | ID: mdl-37646809
3.
Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial.
N Engl J Med
; 382(6): 503-513, 2020 02 06.
Artigo
em Inglês
| MEDLINE | ID: mdl-31995683
4.
Developing a Pan-European Technical Standard for a Comprehensive High-quality Lung Cancer CT Screening Program. An ERS Technical Standard.
Eur Respir J
; 2023 May 18.
Artigo
em Inglês
| MEDLINE | ID: mdl-37202154
5.
Automated Breast Density Assessment in MRI Using Deep Learning and Radiomics: Strategies for Reducing Inter-Observer Variability.
J Magn Reson Imaging
; 2023 Oct 17.
Artigo
em Inglês
| MEDLINE | ID: mdl-37846440
6.
Image quality of DWI at breast MRI depends on the amount of fibroglandular tissue: implications for unenhanced screening.
Eur Radiol
; 2023 Nov 27.
Artigo
em Inglês
| MEDLINE | ID: mdl-38008743
7.
Low-dose computed tomography lung cancer screening: Clinical evidence and implementation research.
J Intern Med
; 292(1): 68-80, 2022 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-35253286
8.
Early detection of obstructive coronary artery disease in the asymptomatic high-risk population: objectives and study design of the EARLY-SYNERGY trial.
Am Heart J
; 246: 166-177, 2022 04.
Artigo
em Inglês
| MEDLINE | ID: mdl-35038412
9.
Facilitating standardized COVID-19 suspicion prediction based on computed tomography radiomics in a multi-demographic setting.
Eur Radiol
; 32(9): 6384-6396, 2022 Sep.
Artigo
em Inglês
| MEDLINE | ID: mdl-35362751
10.
Using deep learning to safely exclude lesions with only ultrafast breast MRI to shorten acquisition and reading time.
Eur Radiol
; 32(12): 8706-8715, 2022 Dec.
Artigo
em Inglês
| MEDLINE | ID: mdl-35614363
11.
T2* assessment of the three coronary artery territories of the left ventricular wall by different monoexponential truncation methods.
MAGMA
; 35(5): 749-763, 2022 Oct.
Artigo
em Inglês
| MEDLINE | ID: mdl-35437686
12.
AI-Driven Model for Automatic Emphysema Detection in Low-Dose Computed Tomography Using Disease-Specific Augmentation.
J Digit Imaging
; 35(3): 538-550, 2022 06.
Artigo
em Inglês
| MEDLINE | ID: mdl-35182291
13.
Evaluation of a novel deep learning-based classifier for perifissural nodules.
Eur Radiol
; 31(6): 4023-4030, 2021 Jun.
Artigo
em Inglês
| MEDLINE | ID: mdl-33269413
14.
Diagnosis, Prevention, and Treatment of Thromboembolic Complications in COVID-19: Report of the National Institute for Public Health of the Netherlands.
Radiology
; 297(1): E216-E222, 2020 10.
Artigo
em Inglês
| MEDLINE | ID: mdl-32324101
15.
Cardiac T2 * mapping: Techniques and clinical applications.
J Magn Reson Imaging
; 52(5): 1340-1351, 2020 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-31837078
16.
Early detection of heart function abnormality by native T1: a comparison of two T1 quantification methods.
Eur Radiol
; 30(1): 652-662, 2020 Jan.
Artigo
em Inglês
| MEDLINE | ID: mdl-31410603
17.
Early imaging biomarkers of lung cancer, COPD and coronary artery disease in the general population: rationale and design of the ImaLife (Imaging in Lifelines) Study.
Eur J Epidemiol
; 35(1): 75-86, 2020 Jan.
Artigo
em Inglês
| MEDLINE | ID: mdl-31016436
18.
Design, Implementation, and Validation of a Pulsatile Heart Phantom Pump.
J Digit Imaging
; 33(5): 1301-1305, 2020 10.
Artigo
em Inglês
| MEDLINE | ID: mdl-32779017
19.
Assessment of Dynamic Change of Coronary Artery Geometry and Its Relationship to Coronary Artery Disease, Based on Coronary CT Angiography.
J Digit Imaging
; 33(2): 480-489, 2020 04.
Artigo
em Inglês
| MEDLINE | ID: mdl-31745678
20.
Probability of cancer in lung nodules using sequential volumetric screening up to 12 months: the UKLS trial.
Thorax
; 74(8): 761-767, 2019 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-31028232