M. Goeller

发表

Fully Automated CT Quantification of Epicardial Adipose Tissue by Deep Learning: A Multicenter Study.

D. Dey, D. Berman, S. Achenbach, 2019, Radiology. Artificial intelligence.

Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium, and epicardial adipose tissue: a prospective study.

Xi Chen, D. Dey, D. Berman, 2019, Cardiovascular research.

Cardiac CT: Technological Advances in Hardware, Software, and Machine Learning Applications

D. Dey, F. Commandeur, M. Goeller, 2018, Current Cardiovascular Imaging Reports.

Influence of reconstruction kernels on the accuracy of CT-derived fractional flow reserve

S. Achenbach, D. Bittner, M. Marwan, 2021, European Radiology.

Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium, and epicardial adipose tissue: a prospective study.

Xi Chen, D. Dey, H. Gransar, 2019, Cardiovascular research.

Early-onset coronary atherosclerosis in patients with low levels of omega-3 fatty acids

D. Bittner, M. Marwan, S. Achenbach, 2020, European Journal of Clinical Nutrition.

Pericoronary adipose tissue CT attenuation and its association with serum levels of atherosclerosis-relevant inflammatory mediators, coronary calcification and major adverse cardiac events.

D. Dey, S. Achenbach, D. Bittner, 2021, Journal of cardiovascular computed tomography.

Deep Learning–Based Quantification of Epicardial Adipose Tissue Volume and Attenuation Predicts Major Adverse Cardiovascular Events in Asymptomatic Subjects

D. Dey, D. Berman, S. Achenbach, 2020, Circulation. Cardiovascular imaging.

Tissue by Deep Learning: A Multicenter Study

Xi Chen, D. Dey, S. Achenbach, 2019 .

Diagnostic Accuracy of Noncontrast Self-navigated Free-breathing MR Angiography versus CT Angiography: A Prospective Study in Pediatric Patients with Suspected Anomalous Coronary Arteries.

Virginia W. Lesslie, T. Vogl, U. Schoepf, 2019, Academic radiology.

Relationship between changes in pericoronary adipose tissue attenuation and coronary plaque burden quantified from coronary computed tomography angiography.

D. Dey, D. Berman, S. Achenbach, 2019, European heart journal cardiovascular Imaging.

High levels of eicosapentaenoic acid are associated with lower pericoronary adipose tissue attenuation as measured by coronary CTA.

D. Dey, S. Achenbach, Y. Zopf, 2020, Atherosclerosis.

Artificial Intelligence-based quantification of atherosclerotic plaque and stenosis from coronary computed tomography angiography using a novel method

D. Dey, S. Achenbach, M. Dweck, 2022, Medical Imaging.

Non-invasive fractional flow reserve in vessels without severe obstructive stenosis is associated with coronary plaque burden.

D. Dey, D. Berman, H. Gransar, 2018, Journal of cardiovascular computed tomography.

Differences of inflammatory cytokine profile in patients with vulnerable plaque: A coronary CTA study.

D. Dey, S. Achenbach, D. Bittner, 2022, Atherosclerosis.

Quantification of epicardial adipose tissue by cardiac CT: Influence of acquisition parameters and contrast enhancement.

S. Achenbach, D. Bittner, M. Hell, 2019, European journal of radiology.

Pericoronary Adipose Tissue Computed Tomography Attenuation and High-Risk Plaque Characteristics in Acute Coronary Syndrome Compared With Stable Coronary Artery Disease

D. Dey, D. Berman, S. Achenbach, 2018, JAMA cardiology.

Computed Tomography-derived Characterization of Pericoronary, Epicardial, and Paracardial Adipose Tissue and Its Association With Myocardial Ischemia as Assessed by Computed Fractional Flow Reserve

D. Dey, D. Bittner, M. Marwan, 2021, Journal of thoracic imaging.

Imaging of the Pericoronary Adipose Tissue (PCAT) Using Cardiac Computed Tomography: Modern Clinical Implications.

D. Dey, S. Achenbach, M. Marwan, 2021, Journal of thoracic imaging.

Ethnic differences in coronary anatomy, left ventricular mass and CT-derived fractional flow reserve.

D. Dey, S. Achenbach, J. Leipsic, 2020, Journal of cardiovascular computed tomography.

Pericoronary adipose tissue and quantitative global non-calcified plaque characteristics from CT angiography do not differ in matched South Asian, East Asian and European-origin Caucasian patients with stable chest pain.

D. Dey, S. Achenbach, B. Ko, 2020, European journal of radiology.

Comparison of Coronary Atherosclerotic Plaque Burden and Composition as Assessed on Coronary Computed Tomography Angiography in East Asian and European-Origin Caucasians.

D. Dey, S. Achenbach, B. Ko, 2019, The American journal of cardiology.

Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study

D. Dey, S. Achenbach, H. Gransar, 2022, The Lancet. Digital health.

Machine learning integration of circulating and imaging biomarkers for explainable patient-specific prediction of cardiac events: A prospective study.

D. Dey, D. Berman, S. Achenbach, 2020, Atherosclerosis.

Carotid plaque composition by CT angiography in asymptomatic subjects: a head-to-head comparison to ultrasound

D. Dey, B. Nørgaard, J. Gram, 2019, European Radiology.

Deep learning-based stenosis quantification from coronary CT angiography

Piotr J. Slomka, Daniel S. Berman, Damini Dey, 2019, Medical Imaging: Image Processing.

Deep Learning for Quantification of Epicardial and Thoracic Adipose Tissue From Non-Contrast CT

Piotr J. Slomka, Daniel S. Berman, Damini Dey, 2018, IEEE Transactions on Medical Imaging.

Integrated prediction of lesion-specific ischaemia from quantitative coronary CT angiography using machine learning: a multicentre study

Piotr J. Slomka, Daniel S. Berman, Damini Dey, 2018, European Radiology.

Epicardial adipose tissue density and volume are related to subclinical atherosclerosis, inflammation and major adverse cardiac events in asymptomatic subjects.

Xi Chen, D. Dey, D. Berman, 2017, Journal of cardiovascular computed tomography.

Diagnostic accuracy of low and high tube voltage coronary CT angiography using an X-ray tube potential-tailored contrast medium injection protocol

Brian E. Jacobs, U. Schoepf, T. Vogl, 2018, European Radiology.

Radiomics-Based Precision Phenotyping Identifies Unstable Coronary Plaques From Computed Tomography Angiography.

D. Dey, S. Achenbach, P. Slomka, 2022, JACC. Cardiovascular imaging.

Computed tomography–based pericoronary adipose tissue attenuation in patients undergoing TAVR: a novel method for risk assessment

E. Nagel, D. Leistner, V. Puntmann, 2023, Frontiers in Cardiovascular Medicine.

Deep Learning From Coronary Computed Tomography Angiography for Atherosclerotic Plaque and Stenosis Quantification and Cardiac Risk Prediction

D. Dey, D. Berman, S. Achenbach, 2021, SSRN Electronic Journal.

Direct head-to-head comparison of convolutional long short-term memory and transformer networks for artificial Intelligence-based quantification of atherosclerotic plaque and stenosis from coronary CT angiography

D. Dey, P. Slomka, M. Dweck, 2023, Medical Imaging.

Is PCAT CT Attenuation the 'Game Changer' in the Prediction of Death and Myocardial Infarction?

M. Marwan, M. Goeller, 2021, JACC. Cardiovascular imaging.

The Munich-Transarterial Chemoembolisation Score Holds Superior Prognostic Capacities Compared to TACE-Tailored Modifications of 9 Established Staging Systems for Hepatocellular Carcinoma

J. Trojan, A. Gerbes, F. Kolligs, 2018, Digestion.

Diagnostic accuracy of low and high tube voltage coronary CT angiography using an X-ray tube potential-tailored contrast medium injection protocol

Brian E. Jacobs, U. Schoepf, T. Vogl, 2018, European Radiology.