BACK TO INDEX

Publications of Shuman Jia

Thesis

  1. Shuman Jia. Population-based models of shape, structure, and deformation in atrial fibrillation. Theses, COMUE Université Côte d'Azur (2015 - 2019), December 2019. Keyword(s): Cardiac image analysis, Atrial fibrillation, Segmentation, Fat, Statistical shape analysis, Parallel transport, Analyse d'images cardiaques, Fibrillation auriculaire, Segmentation, Graisse, Analyse statistique des formes, Transport parallèle. [bibtex-entry]


Articles in journal, book chapters

  1. Shuman Jia, Hubert Nivet, Josquin Harrison, Xavier Pennec, Claudia Camaioni, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. Left atrial shape is independent predictor of arrhythmia recurrence after catheter ablation for atrial fibrillation: A shape statistics study. Heart Rhythm O2, 2(6):622-632, December 2021. Keyword(s): Atrial fibrillation, Catheter ablation, CT, Left atrial shape, Recurrence, Statistical shape modeling. [bibtex-entry]


  2. Rashed Karim, Lauren-Emma Blake, Jiro Inoue, Qian Tao, Shuman Jia, R. James James Housden, Pranav Bhagirath, Jean-Luc Duval, Marta Varela, Jonathan Behar, Loïc Cadour, Rob J van Der Geest, Hubert Cochet, Maria Drangova, Maxime Sermesant, Reza Razavi, Oleg Aslanidi, Ronak Rajani, and Kawal S. Rhode. Algorithms for left atrial wall segmentation and thickness -- Evaluation on an open-source CT and MRI image database. Medical Image Analysis, 50:36 - 53, December 2018. Keyword(s): Myocardium, Left atrial wall thickness, Left atrium, Atrial fibrillation. [bibtex-entry]


Conference articles

  1. Marta Nuñez-Garcia, Nicolas Cedilnik, Shuman Jia, Hubert Cochet, Marco Lorenzi, and Maxime Sermesant. Estimation of imaging biomarker's progression in post-infarct patients using cross-sectional data. In STACOM 2020 - 11th International Workshop on Statistical Atlases and Computational Models of the Heart, Lima, Peru, pages p.108-116, October 2020. Keyword(s): Post-infarct cardiac remodeling, Ventricular arrhythmia, Cross-sectional data, Disease progression modeling. [bibtex-entry]


  2. Marta Nuñez-Garcia, Nicolas Cedilnik, Shuman Jia, Maxime Sermesant, and Hubert Cochet. Automatic multiplanar CT reformatting from trans-axial into left ventricle short-axis view. In STACOM 2020 - 11th International Workshop on Statistical Atlases and Computational Models of the Heart, Lima, Peru, pages p.108-116, October 2020. Keyword(s): Automatic image reformatting, Short-axis view, Deep learning segmentation, Cardiac imaging. [bibtex-entry]


  3. Nicolas Cedilnik, Shuman Jia, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. Automatic non-invasive substrate analysis from CT images in post-infarction VT. In EHRA 2019 - European Heart Rhythm Association, volume 21, Lisbonne, Portugal, pages 720-739, March 2019. [bibtex-entry]


  4. Nicolas Guigui, Shuman Jia, Maxime Sermesant, and Xavier Pennec. Symmetric Algorithmic Components for Shape Analysis with Diffeomorphisms. In GSI 2019 - 4th conference on Geometric Science of Information, volume Lecture Notes in Computer Science 11712 of Proceedings of Geometric Science of Information, Toulouse, France, pages 759-768, August 2019. F. Nielsen and F. Barbaresco, Springer. Keyword(s): Symmetric Spaces, Parallel Transport, Shape Registration. [bibtex-entry]


  5. Shuman Jia, Antoine Despinasse, Zihao Wang, Hervé Delingette, Xavier Pennec, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. Automatically Segmenting the Left Atrium from Cardiac Images Using Successive 3D U-Nets and a Contour Loss. In STACOM: Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges, volume 11395 of LNCS, Granada, Spain, pages 221-229, September 2018. Keyword(s): distance map, ensemble prediction, loss function, contour loss, left atrium, deep learning, segmentation, 3D U-Net. [bibtex-entry]


  6. Shuman Jia, Nicolas Duchateau, Pamela Moceri, Maxime Sermesant, and Xavier Pennec. Parallel Transport of Surface Deformations from Pole Ladder to Symmetrical Extension. In Shape in Medical Imaging. ShapeMI 2018., volume 11167 of LNCS, Granada, Spain, pages 116-124, September 2018. Springer. [bibtex-entry]


  7. Shuman Jia, Claudia Camaioni, Marc-Michel Rohé, Pierre Jaïs, Xavier Pennec, Hubert Cochet, and Maxime Sermesant. Prediction of Post-Ablation Outcome in Atrial Fibrillation Using Shape Parameterization and Partial Least Squares Regression. In FIMH 2017 - International Conference on Functional Imaging and Modeling of the Heart, volume 10263 of Lecture Notes in Computer Science, Toronto, Canada, pages 314 - 321, June 2017. Keyword(s): atrial fibrillation, catheter ablation, post-ablation outcome, left atrial remodeling, statistical shape analysis, partial least squares, regression. [bibtex-entry]


  8. Shuman Jia, Loïc Cadour, Hubert Cochet, and Maxime Sermesant. STACOM-SLAWT Challenge: Left Atrial Wall Segmentation and Thickness Measurement Using Region Growing and Marker-Controlled Geodesic Active Contour. In 7th International Statistical Atlases and Computational Modeling of the Heart (STACOM) Workshop, Held in Conjunction with MICCAI 2016, volume 10124 of LNCS, Athens, Greece, pages 211-219, October 2016. Springer. Keyword(s): geodesic active contour, atrial fibrillation, left atrial wall thickness, 3-dimensional image segmentation, cardiac computed tomography (CT), region growing. [bibtex-entry]



BACK TO INDEX

Disclaimer:

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All person copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Les documents contenus dans ces répertoires sont rendus disponibles par les auteurs qui y ont contribué en vue d'assurer la diffusion à temps de travaux savants et techniques sur une base non-commerciale. Les droits de copie et autres droits sont gardés par les auteurs et par les détenteurs du copyright, en dépit du fait qu'ils présentent ici leurs travaux sous forme électronique. Les personnes copiant ces informations doivent adhérer aux termes et contraintes couverts par le copyright de chaque auteur. Ces travaux ne peuvent pas être rendus disponibles ailleurs sans la permission explicite du détenteur du copyright.

Last modified: Thu Apr 25 00:30:04 2024
Author: epione-publi.

This document was translated from BibTEX by bibtex2html