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Publications of Julian Krebs

Thesis

  1. Julian Krebs. Robust medical image registration and motion modeling based on machine learning. Theses, Université Côte d'Azur, June 2020. Keyword(s): Medical Image Registration, Motion Modeling, Machine Learning, Varitiaonal Autoencoder, Sudden Cardiac Death Risk, Recalage d'images médicales, Modélisation du mouvement, Apprentissage profond. [bibtex-entry]


Articles in journal, book chapters

  1. Julian Krebs, Hervé Delingette, Nicholas Ayache, and Tommaso Mansi. Learning a Generative Motion Model from Image Sequences based on a Latent Motion Matrix. IEEE Transactions on Medical Imaging, February 2021. Keyword(s): motion model, deformable registration, conditional variational autoencoder, gaussian process, latent variable model, motion interpolation, motion simulation, tracking. [bibtex-entry]


  2. Julian Krebs, Tommaso Mansi, Hervé Delingette, Bin Lou, Joao Lima, Susumu Tao, Luisa Ciuffo, Sanaz Norgard, Barbara Butcher, Wei Lee, Ela Chamera, Timm-Michael Dickfeld, Michael Stillabower, Joseph Marine, Robert Weiss, Gordon Tomaselli, Henry Halperin, Katherine Wu, and Hiroshi Ashikaga. CinE caRdiac magneTic resonAnce to predIct veNTricular arrhYthmia (CERTAINTY). Scientific Reports, 11(1):22683, November 2021. Keyword(s): Cardiac device therapy, Ventricular fibrillation, Ventricular tachycardia. [bibtex-entry]


  3. Julian Krebs, Hervé Delingette, Boris Mailhé, Nicholas Ayache, and Tommaso Mansi. Learning a Probabilistic Model for Diffeomorphic Registration. IEEE Transactions on Medical Imaging, pp 2165-2176, February 2019. Keyword(s): deformable registration, deformation transport, latent variable model, probabilistic encoding, conditional variational autoencoder, deep learning. [bibtex-entry]


Conference articles

  1. Tania Bacoyannis, Julian Krebs, Nicolas Cedilnik, Hubert Cochet, and Maxime Sermesant. Deep Learning Formulation of ECGI for Data-driven Integration of Spatiotemporal Correlations and Imaging Information. In FIMH 2019 - 10th International Conference on Functional Imaging and Modeling of the Heart, volume LNCS 11504, Bordeaux, France, pages 20-28, June 2019. Springer. Keyword(s): ECGI, Deep learning, Generative Model, Simulation. [bibtex-entry]


  2. Julian Krebs, Tommaso Mansi, Nicholas Ayache, and Hervé Delingette. Probabilistic Motion Modeling from Medical Image Sequences: Application to Cardiac Cine-MRI. In STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart, Shenzhen, China, October 2019. Note: Probabilistic Motion Model, Motion Tracking, Temporal Super-Resolution, Diffeomorphic Registration, Temporal Variational Autoencoder. [bibtex-entry]


  3. Julian Krebs, Tommaso Mansi, Boris Mailhé, Nicholas Ayache, and Hervé Delingette. Unsupervised Probabilistic Deformation Modeling for Robust Diffeomorphic Registration. In Deep Learning in Medical Image Analysis (MICCAI workshop), Granada, Spain, September 2018. Keyword(s): Image registration, Deep learning, Medical imaging analysis. [bibtex-entry]


  4. Julian Krebs, Tommaso Mansi, Hervé Delingette, Li Zhang, Florin C Ghesu, Shun Miao, Andreas Maier, Nicholas Ayache, Rui Liao, and Ali Kamen. Robust non-rigid registration through agent-based action learning. In Medical Image Computing and Computer Assisted Interventions (MICCAI), Medical Image Computing and Computer Assisted Intervention -- MICCAI 2017, Quebec, Canada, pages 344-352, September 2017. Springer International Publishing. Keyword(s): reinforcement learning, Image registration. [bibtex-entry]


Patents, standards

  1. Julian Krebs, Hiroshi Ashikaga, Tommaso Mansi, Bin Lou, Katherine Chih-Ching Wu, and Henry Halperin. Risk prediction for sudden cardiac death from image derived cardiac motion and structure features. US20210059612A1, United States, March 2021. [bibtex-entry]


  2. Julian Krebs, Tommaso Mansi, and Bin Lou. Patient specific risk prediction of cardiac events from image-derived cardiac function features. US20210057104A1, United States, February 2021. [bibtex-entry]


  3. Julian Krebs and Tommaso Mansi. Method and System for Deep Motion Model Learning in Medical Images. US20200090345A1, United States, March 2020. [bibtex-entry]


  4. Julian Krebs, Tommaso Mansi, Hervé Delingette, and Nicholas Ayache. Probabilist Motion Model for Generating Medical Images or Medical Image Sequences. US16834269, United States, October 2020. [bibtex-entry]


  5. Julian Krebs, Hervé Delingette, Nicholas Ayache, Tommaso Mansi, and Shun Miao. Medical Imaging Diffeomorphic Registration based on Machine Learning. US 2019/0205766 A1, United States, July 2019. [bibtex-entry]



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