H
Hortense A. Kirisli
Researcher at Erasmus University Rotterdam
Publications - 25
Citations - 761
Hortense A. Kirisli is an academic researcher from Erasmus University Rotterdam. The author has contributed to research in topics: Coronary artery disease & Segmentation. The author has an hindex of 13, co-authored 25 publications receiving 650 citations. Previous affiliations of Hortense A. Kirisli include Leiden University Medical Center & Leiden University.
Papers
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Journal ArticleDOI
Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in computed tomography angiography.
Hortense A. Kirisli,Michiel Schaap,Coert Metz,Anoeshka S. Dharampal,Willem B. Meijboom,Stella-Lida Papadopoulou,Admir Dedic,Koen Nieman,M. A. de Graaf,M. F. L. Meijs,M. J. Cramer,A. Broersen,Suheyla Cetin,Abouzar Eslami,Leonardo Flórez-Valencia,K.L. Lor,Bogdan J. Matuszewski,I. Melki,I. Melki,B. Mohr,Ilkay Oksuz,Rahil Shahzad,Rahil Shahzad,Chunliang Wang,Pieter H. Kitslaar,Gozde Unal,Amin Katouzian,Amin Katouzian,Maciej Orkisz,Chung-Ming Chen,Frédéric Precioso,Laurent Najman,S. Masood,Devrim Unay,L.J. van Vliet,Rodrigo Moreno,Roman Goldenberg,E. Vuçini,Gabriel P. Krestin,Wiro J. Niessen,Wiro J. Niessen,T. van Walsum +41 more
TL;DR: Results show that some of the current stenosis detection/quantification algorithms may be used for triage or as a second-reader in clinical practice, and that automatic lumen segmentation is possible with a precision similar to that obtained by experts.
Journal ArticleDOI
Evaluation of a multi-atlas based method for segmentation of cardiac CTA data: a large-scale, multicenter, and multivendor study
Hortense A. Kirisli,Michiel Schaap,Stefan Klein,Stella-Lida Papadopoulou,M. Bonardi,C. H. Chen,Annick C. Weustink,Nico R. Mollet,E.-J. Vonken,R.J. van der Geest,T. van Walsum,Wiro J. Niessen +11 more
TL;DR: The accuracy and robustness of cardiac chamber delineation using a multiatlas based segmentation method on multicenter and multivendor CTA data was investigated and the method demonstrated by successfully applying the method to 1420 multicenter/multivendor data sets.
Journal ArticleDOI
Automatic segmentation, detection and quantification of coronary artery stenoses on CTA
Rahil Shahzad,Hortense A. Kirisli,Coert Metz,Hui Tang,Hui Tang,Michiel Schaap,Lucas J. van Vliet,Wiro J. Niessen,Wiro J. Niessen,Theo van Walsum +9 more
TL;DR: The method achieved a detection sensitivity of 29 % and a positive predictive value (PPV) of 24 % as compared to quantitative coronary angiography (QCA), and a sensitivity and a PPV of 21 %" as compared manual assessment based on consensus reading of CTA by 3 observers.
Proceedings ArticleDOI
Fully automatic cardiac segmentation from 3D CTA data: a multi-atlas based approach
Hortense A. Kirisli,Michiel Schaap,Stefan Klein,Lisan A. Neefjes,Annick C. Weustink,Theo van Walsum,Wiro J. Niessen,Wiro J. Niessen +7 more
TL;DR: The whole heart segmentation method proposed can be used for visualization of the coronary arteries and for obtaining a region of interest for subsequent segmentation of the coronaries, ventricles and atria.
Journal ArticleDOI
Automatic quantification of epicardial fat volume on non-enhanced cardiac CT scans using a multi-atlas segmentation approach
Rahil Shahzad,Daniel Bos,Coert Metz,Alexia Rossi,Hortense A. Kirisli,Aad van der Lugt,Stefan Klein,Jacqueline C.M. Witteman,Pim J. de Feyter,Wiro J. Niessen,Lucas J. van Vliet,Theo van Walsum +11 more
TL;DR: The authors developed a fully automatic method that is capable of segmenting the pericardium and quantifying epicardial fat on non-enhanced cardiac CT scans and demonstrated the feasibility of using this method to replace manual annotations by showing that the automatic method performs as good as manual annotation on a large dataset.