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Publications of Jan Margeta

Thesis

  1. Jan Margeta. Machine Learning for Simplifying the Use of Cardiac Image Databases. Theses, Ecole Nationale Supérieure des Mines de Paris, December 2015. [bibtex-entry]


Articles in journal, book chapters

  1. Jan Margeta, Antonio Criminisi, Rocio Cabrera Lozoya, Daniel C. Lee, and Nicholas Ayache. Fine-tuned convolutional neural nets for cardiac MRI acquisition plane recognition. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, August 2015. Note: This is an electronic version of an article published inComputer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualizationon 13 August 2015, by Taylor & Francis, DOI: 10.1080/21681163.2015.1061448.Available online at: http://www.tandfonline.com/10.1080/21681163.2015.1061448. Keyword(s): Transfer learning, Fine-tuning, SSFP, Planes of acquisition, Machine learning, Cardiac magnetic resonance, Convolutional neural networks, Magnetic resonance, Cardiac imaging, Deep learning. [bibtex-entry]


  2. Catalina Tobon-Gomez, Arjan J. Geers, Jochen Peters, Jürgen Weese, Karen Pinto, Rashed Karim, Mohammed Ammar, Abdelaziz Daoudi, Jan Margeta, Zulma Sandoval, Birgit Stender, Yefeng Zheng, Maria A. Zuluaga, Julian Betancur, Nicholas Ayache, Mohammed Amine Chikh, Jean-Louis Dillenseger, Michael B. Kelm, Saïd Mahmoudi, Sébastien Ourselin, Alexander Schlaefer, Tobias Schaeffter, Reza Razavi, and Kawal S. Rhode. Benchmark for Algorithms Segmenting the Left Atrium From 3D CT and MRI Datasets. IEEE Transactions on Medical Imaging, 34(7):1460-1473, July 2015. Keyword(s): Benchmark testing, automatic segmentations, atrial fibrillation ablation guidance, anatomical regions, 3D CT datasets, Left Atrial Segmentation Challenge, left atrial surface, ground truth, image segmentation, LA appendage trunk, LASC, LA segmentation, left atrial anatomy, left atrium, Magnetic Resonance Imaging, Measurement, medical image processing, MRI datasets, multiple input data, physiological models, pulmonary vein proximal sections, region growing approach, Shape, standardisation framework, statistical analysis, statistical models, biomedical MRI, biophysical modelling, blood vessels, cardiovascular disease, cardiovascular system, Computed Tomography, computerised tomography, diseases, Educational institutions, electroanatomical mapping systems, evaluation code, fibrosis quantification. [bibtex-entry]


  3. Avan Suinesiaputra, Brett Cowan, Ahmed O. Al-Agamy, Mustafa A. Alattar, Nicholas Ayache, Ahmed S. Fahmy, Ayman M. Khalifa, Pau Medrano-Gracia, Marie-Pierre Jolly, Alan H. Kadish, Daniel C. Lee, Jan Margeta, Simon K. Warfield, and Alistair Young. A Collaborative Resource to Build Consensus for Automated Left Ventricular Segmentation of Cardiac MR Images. Medical Image Analysis, 18(1):50-62, 2014. [bibtex-entry]


Conference articles

  1. Héloïse Bleton, Jan Margeta, Herve Lombaert, Hervé Delingette, and Nicholas Ayache. Myocardial Infarct Localization using Neighborhood Approximation Forests. In Statistical Atlases and Computational Modeling of the Heart (STACOM 2015), Munich, Germany, October 2015. Keyword(s): Machine Learning, Neighbourhood Approximation Forests, myocardial infarction, wall thickness. [bibtex-entry]


  2. Rocio Cabrera Lozoya, Jan Margeta, Loic Le Folgoc, Yuki Komatsu, Berte Benjamin, Jatin Relan, Hubert Cochet, Michel Haïssaguerre, Pierre Jais, Nicholas Ayache, and Maxime Sermesant. Confidence-based Training for Clinical Data Uncertainty in Image-based Prediction of Cardiac Ablation Targets. In bigMCV Workshop MICCAI 2014, Boston, United States, September 2014. [bibtex-entry]


  3. Jan Margeta, Antonio Criminisi, Daniel C. Lee, and Nicholas Ayache. Recognizing cardiac magnetic resonance acquisition planes. In MIUA - Medical Image Understanding and Analysis Conference - 2014, London, United Kingdom, July 2014. Reyes-Aldasoro, Constantino Carlos and Slabaugh, Gregory. Keyword(s): random forests, cardiac MR. [bibtex-entry]


  4. Jan Margeta, Kristin Mcleod, Antonio Criminisi, and Nicholas Ayache. Decision forests for segmentation of left atrium from 3D MRI. In 4th International Workshop on Statistical Atlases and Computational Models of the Heart, Nagoya, Japan, September 2013. [bibtex-entry]


  5. Jan Margeta, Ezequiel Geremia, Antonio Criminisi, and Nicholas Ayache. Layered Spatio-temporal Forests for Left Ventricle Segmentation from 4D Cardiac MRI Data. In Proceedings of STACOM Workshop at MICCAI 2011, September 2011. Springer. [bibtex-entry]



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Last modified: Fri Aug 7 12:30:05 2020
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