Ghent University Academic Bibliography

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- Conference Paper
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Curriculum deep reinforcement learning with different exploration strategies : a feasibility study on cardiac landmark detection

Patricio Astudillo, Peter Mortier, Matthieu De Beule and Francis wyffels (UGent)

(2020) PROCEEDINGS OF THE 13TH INTERNATIONAL JOINT CONFERENCE ON BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES, VOL 2: BIOIMAGING. p.37-45
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- Journal Article
- A1
- open access
Automatic detection of the aortic annular plane and coronary ostia from multidetector computed tomography

Patricio Astudillo, Peter Mortier, Johan Bosmans, Ole De Backer, Peter de Jaegere, Francesco Iannaccone, Matthieu De Beule and Joni Dambre (UGent)

(2020) JOURNAL OF INTERVENTIONAL CARDIOLOGY.
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Towards safe and efficient pre-operative planning of transcatheter mitral valve interventions

Patricio Astudillo, Matthieu De Beule (UGent) , Joni Dambre (UGent) and Peter Mortier (UGent)

(2019) MORPHOLOGIE. 103(343). p.139-147
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Classification of aortic valve morphology using a three-dimensional convolutional neural network

Cameron Dowling, Patricio Astudillo, Stephen Brecker, Matthieu De Beule (UGent) , Peter Mortier (UGent) and Joni Dambre (UGent)

(2019) PCR London Valves, Abstracts.
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Optimization of a transcatheter heart valve frame using patient-specific computer simulation

Giorgia Rocatello, Gianluca De Santis, Sander De Bock, Matthieu De Beule, Patrick Segers (UGent) and Peter Mortier

(2019) CARDIOVASCULAR ENGINEERING AND TECHNOLOGY. 10(3). p.456-468
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- Journal Article
- A1
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Enabling automated device size selection for transcatheter aortic valve implantation

Patricio Astudillo, Peter Mortier, Johan Bosmans, Ole De Backer, Peter De Jaegere, Matthieu De Beule and Joni Dambre (UGent)

(2019) JOURNAL OF INTERVENTIONAL CARDIOLOGY. 2019.
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The impact of size and position of a mechanical expandable transcatheter aortic valve : novel insights through computational modelling and simulation

Giorgia Rocatello, Nahid El Faquir, Ole De Backer, Martin J. Swaans, Azeem Latib, Luca Vicentini, Patrick Segers (UGent) , Matthieu De Beule, Peter de Jaegere and Peter Mortier

(2019) JOURNAL OF CARDIOVASCULAR TRANSLATIONAL RESEARCH. 12(5). p.435-446
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- Conference Paper
- C3
- open access
Towards automated TAVI device size selection using artificial intelligence

Patricio Astudillo, Peter Mortier (UGent) , Matthieu De Beule, Johan Bosmans, Ole De Backer, Peter de Jaegere and Joni Dambre (UGent)

(2018) 5th European Congress on eCardiology and eHealth, Abstracts.
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Detection of the aortic annular plane and coronary ostia from MDCT using deep learning techniques.

Patricio Astudillo, Francesco Iannaccone (UGent) , Peter de Jaegere, Johan Bosmans, Ole De Backer (UGent) , Matthieu De Beule (UGent) , Peter Mortier (UGent) and Joni Dambre (UGent)

(2018) Advanced Techniques and Therapies in Cardiovascular Care, ATTICC 2018, abstracts.
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Patient-specific computer simulation to elucidate the role of contact pressure in the development of new conduction abnormalities after catheter-based implantation of a self-expanding aortic valve

Giorgia Rocatello, Nahid El Faquir, Gianluca De Santis (UGent) , Francesco Iannaccone (UGent) , Johan Bosmans, Ole De Backer, Lars Sondergaard, Patrick Segers (UGent) , Matthieu De Beule (UGent) , Peter de Jaegere, et al.

(2018) CIRCULATION-CARDIOVASCULAR INTERVENTIONS. 11(2).

Academic Bibliography

Curriculum deep reinforcement learning with different exploration strategies : a feasibility study on cardiac landmark detection

Automatic detection of the aortic annular plane and coronary ostia from multidetector computed tomography

Towards safe and efficient pre-operative planning of transcatheter mitral valve interventions

Classification of aortic valve morphology using a three-dimensional convolutional neural network

Optimization of a transcatheter heart valve frame using patient-specific computer simulation

Enabling automated device size selection for transcatheter aortic valve implantation

The impact of size and position of a mechanical expandable transcatheter aortic valve : novel insights through computational modelling and simulation

Towards automated TAVI device size selection using artificial intelligence

Detection of the aortic annular plane and coronary ostia from MDCT using deep learning techniques.

Patient-specific computer simulation to elucidate the role of contact pressure in the development of new conduction abnormalities after catheter-based implantation of a self-expanding aortic valve

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