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Ciudad y territorio : el proceso de poblamiento en Colombia
| Ciudad y territorio : el proceso de poblamiento en Colombia |
| Autore | Zambrano Pantoja Fabio |
| Pubbl/distr/stampa | Institut français d’études andines, 1993 |
| Descrizione fisica | 1 online resource (297 pages) |
| Collana | Travaux de l'IFÉA |
| Soggetto topico |
Sociology & Social History
Social Sciences Communities - Urban Groups |
| Soggetto non controllato |
Colombia
poblamiento |
| ISBN | 2-8218-4501-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | spa |
| Record Nr. | UNINA-9910140112503321 |
Zambrano Pantoja Fabio
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| Institut français d’études andines, 1993 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Le français et les langues d'Europe : Cinquièmes Rencontres de Liré / / Françoise Argod-Dutard
| Le français et les langues d'Europe : Cinquièmes Rencontres de Liré / / Françoise Argod-Dutard |
| Autore | Acker Marieke Van |
| Pubbl/distr/stampa | Rennes, : Presses universitaires de Rennes, 2016 |
| Descrizione fisica | 1 online resource (480 p.) |
| Altri autori (Persone) |
Aguer-SanchizMary
Alberniti-GuillevicLucie Albertini-GuillevicLucie Argod-DutardFrançoise BahuauPascal BaïssusJean-Marc BaratinMarc BaulandeJacques BeaumonDominique BernardOlivier BoislèveJacques BourdelierOlivier BrossierDominique Brunet CanaleOdile CesbronGeorges ChaixGérald CharbonnierJoseph CharlesMartine CharvetPascal ClémentJérôme ColignonJean-Pierre CombeaudBernard CunowYves DahéronDominique DelmolyJacques DepeckerLoïc DreyfusAnne DronneauNicole DubreilLaurence DuclosPascale EssirardJacky FontaineGuy FraileAntoine GapaillardClaude Garnier-CorverFrançoise GhillebaertChristian GodinezMaria GoubierGeneviève GramainMichel GuillouPhilippe Le HardoüinHervé HérisséCécile HermetetAnne-Rachel HualpaPascale de Schuyter IonescuMarina Mureşanu JacqJean-Claude JaninPierre JaunetJean-Luc JombartLoïc LaurentMaryla LeclairBernard LeclercMichel LegrasIsabelle LherbierSoizic LuginbühlOdile L’HénoretLiliane MainguyMarie-Annick MarchéVéronique MathéPhilippe MitterrandFrédéric MoreauMichel MusindeJulien Kilanga NabatCatherine NigoulDaniel NorthXavier PaponPhilippe PaulÉlisabeth PöllBernhard RabaudMichel RosselinIsabelle StaquetDavid Tauzer-SabatelliFrançoise VaumoronJean VerryÉlisabeth VignestRomain WalterHenriette WismanHeinz WismannHeinz WuilmartFrançoise |
| Soggetto topico |
Language & Linguistics (General)
Français (langue) Europe enseignement |
| Soggetto non controllato |
enseignement
Europe Français (langue) |
| ISBN | 2-7535-4587-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Record Nr. | UNINA-9910136979503321 |
|
Acker Marieke Van
|
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| Rennes, : Presses universitaires de Rennes, 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Le français, une langue pour réussir / / Françoise Argod-Dutard
| Le français, une langue pour réussir / / Françoise Argod-Dutard |
| Autore | Amar Yvan |
| Pubbl/distr/stampa | Rennes, : Presses universitaires de Rennes, 2018 |
| Descrizione fisica | 1 online resource (341 p.) |
| Altri autori (Persone) |
Argod-DutardFrançoise
BeaumonDominique BenaNimrod BensaadonNorbert BernardOlivier BerronMarie-Anne Berthelot-GuietKarine BlanchetPhilippe BlavetEmmanuel BottiChristophe BrangerJacqueline BrasLélia Le BrièreThibaud BrivalRoland BrossierDominique BruleyPauline BrunetOdile CanaleOdile ChalleOdile CharlesMartine CharvetPascal ChauvetChristophe ColignonJean-Pierre CunowYves DorientJacques DouzouCatherine DuboisClaude-Gilbert DuboisGeneviève d’AvrilNicolas Danard dit PoiSon FrancalanzaÉric GautierMarc-Édouard GoudaillierJean-Pierre GramainMichel Guédat-BittighofferDelphine HardoüinHervé HénaffCatherine HérisséCécile HuchetJean Jacquet-PfauChristine JaninPierre JaunetJean-Luc LauéChristian LauginieJean Marcel LherbierSoizic L’HénoretLiliane MainguyMarie-Annick MalardMonique Martin-GranelNicolas MorinChristine MusindeJulien Kilanga NeuryPhilippe NorthXavier NowickiJoanna PaulÉlisabeth PothierBéatrice ProtBlandine PruvostJean RabillerBruno RenaudFrançois RobinChristian RobitailleMichel SalhaHabib Ben SallenaveDanièle StéphanBéatrice Tauzer-SabatelliFrançoise TertraisJérôme TruchotClaude VerryÉlisabeth VillaltaCéline WalterHenriette |
| Soggetto topico |
Education
Language & Linguistics (General) langue française apprentissage des langues didactique francophonie |
| Soggetto non controllato |
francophonie
apprentissage des langues langue française didactique |
| ISBN | 2-7535-5738-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Record Nr. | UNINA-9910317653703321 |
|
Amar Yvan
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| Rennes, : Presses universitaires de Rennes, 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Functional Imaging and Modeling of the Heart [[electronic resource] ] : 12th International Conference, FIMH 2023, Lyon, France, June 19–22, 2023, Proceedings / / edited by Olivier Bernard, Patrick Clarysse, Nicolas Duchateau, Jacques Ohayon, Magalie Viallon
| Functional Imaging and Modeling of the Heart [[electronic resource] ] : 12th International Conference, FIMH 2023, Lyon, France, June 19–22, 2023, Proceedings / / edited by Olivier Bernard, Patrick Clarysse, Nicolas Duchateau, Jacques Ohayon, Magalie Viallon |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (734 pages) |
| Disciplina | 658 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Computer Vision |
| ISBN | 3-031-35302-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cardiac multiscale structure -- Cardiac electrophysiology modeling -- Image and shape analysis -- Cardiovascular hemodynamics and CFD -- Cardiac biomechanics -- Clinical applications. |
| Record Nr. | UNISA-996538666203316 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Functional Imaging and Modeling of the Heart : 12th International Conference, FIMH 2023, Lyon, France, June 19–22, 2023, Proceedings / / edited by Olivier Bernard, Patrick Clarysse, Nicolas Duchateau, Jacques Ohayon, Magalie Viallon
| Functional Imaging and Modeling of the Heart : 12th International Conference, FIMH 2023, Lyon, France, June 19–22, 2023, Proceedings / / edited by Olivier Bernard, Patrick Clarysse, Nicolas Duchateau, Jacques Ohayon, Magalie Viallon |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (734 pages) |
| Disciplina | 658 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Computer Vision |
| ISBN | 3-031-35302-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cardiac multiscale structure -- Cardiac electrophysiology modeling -- Image and shape analysis -- Cardiovascular hemodynamics and CFD -- Cardiac biomechanics -- Clinical applications. |
| Record Nr. | UNINA-9910731463003321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges [[electronic resource] ] : 8th International Workshop, STACOM 2017, Held in Conjunction with MICCAI 2017, Quebec City, Canada, September 10-14, 2017, Revised Selected Papers / / edited by Mihaela Pop, Maxime Sermesant, Pierre-Marc Jodoin, Alain Lalande, Xiahai Zhuang, Guang Yang, Alistair Young, Olivier Bernard
| Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges [[electronic resource] ] : 8th International Workshop, STACOM 2017, Held in Conjunction with MICCAI 2017, Quebec City, Canada, September 10-14, 2017, Revised Selected Papers / / edited by Mihaela Pop, Maxime Sermesant, Pierre-Marc Jodoin, Alain Lalande, Xiahai Zhuang, Guang Yang, Alistair Young, Olivier Bernard |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XIII, 260 p. 94 illus.) |
| Disciplina | 611.12 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Image Processing and Computer Vision Artificial Intelligence |
| ISBN | 3-319-75541-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Regular Papers -- Multiview Machine Learning Using an Atlas of Cardiac Cycle Motion -- 1 Introduction -- 2 Materials -- 3 Methods -- 3.1 Motion Atlas Formation -- 3.2 Multiview Classification -- 4 Experiments and Results -- 5 Discussion -- References -- Joint Myocardial Registration and Segmentation of Cardiac BOLD MRI -- 1 Introduction -- 2 Background -- 3 Methods -- 3.1 Dictionary Learning Based Image Segmentation -- 3.2 Graph-Based Joint Optimization -- 3.3 Dictionary Update -- 4 Experimental Results -- 4.1 Data Preparation and Implementation Details -- 4.2 Visual Evaluation -- 4.3 Quantitative Comparison -- 4.4 CAP Dataset -- 5 Conclusion -- References -- Transfer Learning for the Fully Automatic Segmentation of Left Ventricle Myocardium in Porcine Cardiac Cine MR Images -- Abstract -- 1 Introduction -- 2 Method -- 2.1 Data Description -- 2.2 Image Preprocessing -- 2.3 CNN Architecture and Training Setup -- 2.4 Transfer Learning -- 3 Experiments and Results -- 4 Conclusion and Discussions -- References -- Left Atrial Appendage Neck Modeling for Closure Surgery -- 1 Introduction -- 2 LAA Segmentation -- 3 LAA Neck Modeling -- 3.1 Auto-Detection of the Ostium of the LAA -- 3.2 Establishment of the Standard Coordinate System Based on the Ostium Plane -- 3.3 Auto-Building of Circumscribed Cylindrical Model of LAA Neck -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Ground Truth -- 4.3 Evaluation -- 5 Conclusion -- References -- Detection of Substances in the Left Atrial Appendage by Spatiotemporal Motion Analysis Based on 4D-CT -- 1 Introduction -- 2 Method -- 2.1 Extraction of Optical Flow Fields of Adjacent Phase -- 2.2 The Tracking of Key Voxels in Whole Cardiac Cycle -- 2.3 Hierarchical Clustering of All Trajectory Curves.
2.4 Time-Frequency Analysis of the Track Curve of Critical Lumps - to Realize the Stress and Strain Detection of Lumps -- 3 Experiment and Discussion -- 3.1 Dataset -- 3.2 Evaluation and Results -- 4 Conclusion -- References -- Estimation of Healthy and Fibrotic Tissue Distributions in DE-CMR Incorporating CINE-CMR in an EM Algorithm -- 1 Introduction -- 2 Methods -- 3 Experimental Results -- 4 Conclusions -- References -- Multilevel Non-parametric Groupwise Registration in Cardiac MRI: Application to Explanted Porcine Hearts -- 1 Introduction -- 2 Methods -- 2.1 Data Acquisition -- 2.2 Pairwise Registration of the Anatomical MR Images -- 3 Groupwise Registration -- 4 Results -- 5 Future Work and Conclusions -- References -- ACDC Challenge -- GridNet with Automatic Shape Prior Registration for Automatic MRI Cardiac Segmentation -- 1 Introduction -- 2 Our Method -- 2.1 Shape Prior -- 2.2 Loss -- 2.3 Proposed Network -- 3 Experimental Setup and Results -- 3.1 Dataset, Evaluation Criteria, and Other Methods -- 3.2 Experimental Results -- 4 Conclusion -- References -- A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI -- 1 Introduction -- 2 Method -- 2.1 Data Description -- 2.2 Semi-automatic Segmentation -- 2.3 Radiomics Features for Cardiac Diagnosis -- 2.4 Classification Method -- 2.5 Radiomic Feature Selection -- 3 Results -- 4 Conclusions -- References -- Fast Fully-Automatic Cardiac Segmentation in MRI Using MRF Model Optimization, Substructures Tracking and B-Spline Smoothing -- 1 Introduction -- 2 Automatic Localization of the Heart -- 3 Segmentation of an ED Phase Slice in Between Base and Mid-Ventricle -- 4 Segmentation Based on Tracking the Cardiac Substructures in ED Phase -- 5 Segmentation in the ES Phase -- 6 Left Ventricle Epicardial Boundary Smoothing -- 7 Global Results and First Conclusions -- References. Automatic Segmentation and Disease Classification Using Cardiac Cine MR Images -- 1 Introduction -- 2 Data -- 3 Methods -- 3.1 Segmentation -- 3.2 Diagnosis -- 4 Experiments and Results -- 4.1 Segmentation Results -- 4.2 Diagnosis Results -- 5 Discussion and Conclusion -- References -- An Exploration of 2D and 3D Deep Learning Techniques for Cardiac MR Image Segmentation -- 1 Introduction -- 2 Method -- 2.1 Pre-Processing -- 2.2 Network Architectures -- 2.3 Optimisation -- 2.4 Post-Processing -- 3 Experiments and Results -- 3.1 Data -- 3.2 Evaluation Measures -- 3.3 Experiment 1: Comparison of Loss Functions -- 3.4 Experiment 2: Comparison of Network Architectures -- 3.5 Discussion and Conclusion -- References -- Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific Features -- 1 Introduction -- 2 Methods -- 2.1 Cardiac cine-MRI Dataset -- 2.2 Segmentation -- 2.3 Cardiac Disease Classification -- 3 Results -- 4 Discussion -- References -- 2D-3D Fully Convolutional Neural Networks for Cardiac MR Segmentation -- 1 Introduction -- 2 Method -- 2.1 Network Architecture -- 2.2 Dataset, Preprocessing and Augmentation -- 2.3 Training -- 2.4 Optimization Function -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Densely Connected Fully Convolutional Network for Short-Axis Cardiac Cine MR Image Segmentation and Heart Diagnosis Using Random Forest -- 1 Introduction and Related Work -- 2 Our Method -- 2.1 Data Pre-processing Pipeline -- 2.2 Proposed Network Architecture: Densely Connected Fully Convolutional Network (DFCN) -- 2.3 Loss Function -- 2.4 Post-processing -- 2.5 Cardiac Disease Diagnosis -- 3 Experimental Setup and Results -- 3.1 Dataset and Evaluation Criteria -- 3.2 Experimental Results -- 3.3 Conclusion -- References. Class-Balanced Deep Neural Network for Automatic Ventricular Structure Segmentation -- 1 Introduction -- 2 Methodology -- 2.1 Efficient Semantic Labeling with 3D FCN -- 2.2 Transfer Learning from C3D Model -- 2.3 Promote Training with Deep Supervision -- 2.4 Investigation of Class-Balanced Loss -- 3 Experimental Results -- 4 Conclusions -- References -- Automatic Segmentation of LV and RV in Cardiac MRI -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Dataset -- 2.2 Preprocessing -- 2.3 Architecture -- 3 Experimental Results -- 3.1 Implemented Details -- 3.2 Results and Quantitative Analysis with Other Methods -- 4 Conclusion and Discussion -- Acknowledgement -- References -- Automatic Multi-Atlas Segmentation of Myocardium with SVF-Net -- 1 Introduction -- 2 Rigid Alignment by Landmarks Detection -- 3 Non-rigid Diffeomorphic Registration with SVF-Net -- 4 Label Fusion Method -- 5 Results and Discussion -- 6 Conclusion -- References -- MM-WHS Challenge -- 3D Convolutional Networks for Fully Automatic Fine-Grained Whole Heart Partition -- 1 Introduction -- 2 Methodology -- 2.1 Dense Semantic Labeling with 3D FCN -- 2.2 Knowledge Transfer from C3D Model -- 2.3 Promote Training with Deep Supervision -- 2.4 Multi-class Balanced Loss Function -- 3 Experimental Results -- 4 Conclusions -- References -- Multi-label Whole Heart Segmentation Using CNNs and Anatomical Label Configurations -- 1 Introduction -- 2 Method -- 3 Experimental Setup -- 4 Results and Discussion -- 5 Conclusion -- References -- Multi-Planar Deep Segmentation Networks for Cardiac Substructures from MRI and CT -- 1 Introduction -- 2 Multi-Object Multi-Planar CNN (MO-MP-CNN) -- 3 Experimental Results -- 4 Discussion and Conclusion -- References -- Local Probabilistic Atlases and a Posteriori Correction for the Segmentation of Heart Images -- 1 Introduction -- 2 Methods. 2.1 Construction of the a Priori Information -- 2.2 Segmentation -- 2.3 A Posteriori Correction -- 3 Experiments -- 4 Results -- 5 Conclusion -- References -- Hybrid Loss Guided Convolutional Networks for Whole Heart Parsing -- 1 Introduction -- 2 Methodology -- 2.1 Intensity Calibration as Preprocessing -- 2.2 Enhance the Training of 3D FCN -- 2.3 Hybrid Loss Guided Class-Balanced Segmentation -- 3 Experimental Results -- 4 Conclusions -- References -- 3D Deeply-Supervised U-Net Based Whole Heart Segmentation -- 1 Introduction -- 2 Method -- 2.1 Data Pre-processing -- 2.2 Network Architecture -- 3 Experiments and Results -- 3.1 Data -- 3.2 Performance on Training Set -- 3.3 Performance on Testing Set -- 4 Discussion and Conclusion -- References -- MRI Whole Heart Segmentation Using Discrete Nonlinear Registration and Fast Non-local Fusion -- 1 Introduction and Related Work -- 2 Discrete Registration -- 3 Non-local Label Fusion -- 4 Multi-label Random Walk Regularisation -- 5 Discussion and Conclusion -- References -- Automatic Whole Heart Segmentation Using Deep Learning and Shape Context -- 1 Introduction -- 2 Methods -- 2.1 2.5D Segmentation Using Orthogonal U-Nets -- 2.2 Shape Context Generation -- 2.3 Shape-Context Guided U-Net -- 2.4 Implementation Details -- 3 Results -- 4 Discussion and Conclusion -- References -- Automatic Whole Heart Segmentation in CT Images Based on Multi-atlas Image Registration -- Abstract -- 1 Introduction -- 2 Methodology -- 2.1 A Three-Step Multi-atlas-Based Whole Heart Segmentation -- 2.2 Multiple Atlas Images -- 3 Experimental Results -- 4 Conclusion -- References -- Author Index. |
| Record Nr. | UNISA-996465519703316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges : 8th International Workshop, STACOM 2017, Held in Conjunction with MICCAI 2017, Quebec City, Canada, September 10-14, 2017, Revised Selected Papers / / edited by Mihaela Pop, Maxime Sermesant, Pierre-Marc Jodoin, Alain Lalande, Xiahai Zhuang, Guang Yang, Alistair Young, Olivier Bernard
| Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges : 8th International Workshop, STACOM 2017, Held in Conjunction with MICCAI 2017, Quebec City, Canada, September 10-14, 2017, Revised Selected Papers / / edited by Mihaela Pop, Maxime Sermesant, Pierre-Marc Jodoin, Alain Lalande, Xiahai Zhuang, Guang Yang, Alistair Young, Olivier Bernard |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XIII, 260 p. 94 illus.) |
| Disciplina | 611.12 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Image Processing and Computer Vision Artificial Intelligence |
| ISBN | 3-319-75541-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Regular Papers -- Multiview Machine Learning Using an Atlas of Cardiac Cycle Motion -- 1 Introduction -- 2 Materials -- 3 Methods -- 3.1 Motion Atlas Formation -- 3.2 Multiview Classification -- 4 Experiments and Results -- 5 Discussion -- References -- Joint Myocardial Registration and Segmentation of Cardiac BOLD MRI -- 1 Introduction -- 2 Background -- 3 Methods -- 3.1 Dictionary Learning Based Image Segmentation -- 3.2 Graph-Based Joint Optimization -- 3.3 Dictionary Update -- 4 Experimental Results -- 4.1 Data Preparation and Implementation Details -- 4.2 Visual Evaluation -- 4.3 Quantitative Comparison -- 4.4 CAP Dataset -- 5 Conclusion -- References -- Transfer Learning for the Fully Automatic Segmentation of Left Ventricle Myocardium in Porcine Cardiac Cine MR Images -- Abstract -- 1 Introduction -- 2 Method -- 2.1 Data Description -- 2.2 Image Preprocessing -- 2.3 CNN Architecture and Training Setup -- 2.4 Transfer Learning -- 3 Experiments and Results -- 4 Conclusion and Discussions -- References -- Left Atrial Appendage Neck Modeling for Closure Surgery -- 1 Introduction -- 2 LAA Segmentation -- 3 LAA Neck Modeling -- 3.1 Auto-Detection of the Ostium of the LAA -- 3.2 Establishment of the Standard Coordinate System Based on the Ostium Plane -- 3.3 Auto-Building of Circumscribed Cylindrical Model of LAA Neck -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Ground Truth -- 4.3 Evaluation -- 5 Conclusion -- References -- Detection of Substances in the Left Atrial Appendage by Spatiotemporal Motion Analysis Based on 4D-CT -- 1 Introduction -- 2 Method -- 2.1 Extraction of Optical Flow Fields of Adjacent Phase -- 2.2 The Tracking of Key Voxels in Whole Cardiac Cycle -- 2.3 Hierarchical Clustering of All Trajectory Curves.
2.4 Time-Frequency Analysis of the Track Curve of Critical Lumps - to Realize the Stress and Strain Detection of Lumps -- 3 Experiment and Discussion -- 3.1 Dataset -- 3.2 Evaluation and Results -- 4 Conclusion -- References -- Estimation of Healthy and Fibrotic Tissue Distributions in DE-CMR Incorporating CINE-CMR in an EM Algorithm -- 1 Introduction -- 2 Methods -- 3 Experimental Results -- 4 Conclusions -- References -- Multilevel Non-parametric Groupwise Registration in Cardiac MRI: Application to Explanted Porcine Hearts -- 1 Introduction -- 2 Methods -- 2.1 Data Acquisition -- 2.2 Pairwise Registration of the Anatomical MR Images -- 3 Groupwise Registration -- 4 Results -- 5 Future Work and Conclusions -- References -- ACDC Challenge -- GridNet with Automatic Shape Prior Registration for Automatic MRI Cardiac Segmentation -- 1 Introduction -- 2 Our Method -- 2.1 Shape Prior -- 2.2 Loss -- 2.3 Proposed Network -- 3 Experimental Setup and Results -- 3.1 Dataset, Evaluation Criteria, and Other Methods -- 3.2 Experimental Results -- 4 Conclusion -- References -- A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI -- 1 Introduction -- 2 Method -- 2.1 Data Description -- 2.2 Semi-automatic Segmentation -- 2.3 Radiomics Features for Cardiac Diagnosis -- 2.4 Classification Method -- 2.5 Radiomic Feature Selection -- 3 Results -- 4 Conclusions -- References -- Fast Fully-Automatic Cardiac Segmentation in MRI Using MRF Model Optimization, Substructures Tracking and B-Spline Smoothing -- 1 Introduction -- 2 Automatic Localization of the Heart -- 3 Segmentation of an ED Phase Slice in Between Base and Mid-Ventricle -- 4 Segmentation Based on Tracking the Cardiac Substructures in ED Phase -- 5 Segmentation in the ES Phase -- 6 Left Ventricle Epicardial Boundary Smoothing -- 7 Global Results and First Conclusions -- References. Automatic Segmentation and Disease Classification Using Cardiac Cine MR Images -- 1 Introduction -- 2 Data -- 3 Methods -- 3.1 Segmentation -- 3.2 Diagnosis -- 4 Experiments and Results -- 4.1 Segmentation Results -- 4.2 Diagnosis Results -- 5 Discussion and Conclusion -- References -- An Exploration of 2D and 3D Deep Learning Techniques for Cardiac MR Image Segmentation -- 1 Introduction -- 2 Method -- 2.1 Pre-Processing -- 2.2 Network Architectures -- 2.3 Optimisation -- 2.4 Post-Processing -- 3 Experiments and Results -- 3.1 Data -- 3.2 Evaluation Measures -- 3.3 Experiment 1: Comparison of Loss Functions -- 3.4 Experiment 2: Comparison of Network Architectures -- 3.5 Discussion and Conclusion -- References -- Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific Features -- 1 Introduction -- 2 Methods -- 2.1 Cardiac cine-MRI Dataset -- 2.2 Segmentation -- 2.3 Cardiac Disease Classification -- 3 Results -- 4 Discussion -- References -- 2D-3D Fully Convolutional Neural Networks for Cardiac MR Segmentation -- 1 Introduction -- 2 Method -- 2.1 Network Architecture -- 2.2 Dataset, Preprocessing and Augmentation -- 2.3 Training -- 2.4 Optimization Function -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Densely Connected Fully Convolutional Network for Short-Axis Cardiac Cine MR Image Segmentation and Heart Diagnosis Using Random Forest -- 1 Introduction and Related Work -- 2 Our Method -- 2.1 Data Pre-processing Pipeline -- 2.2 Proposed Network Architecture: Densely Connected Fully Convolutional Network (DFCN) -- 2.3 Loss Function -- 2.4 Post-processing -- 2.5 Cardiac Disease Diagnosis -- 3 Experimental Setup and Results -- 3.1 Dataset and Evaluation Criteria -- 3.2 Experimental Results -- 3.3 Conclusion -- References. Class-Balanced Deep Neural Network for Automatic Ventricular Structure Segmentation -- 1 Introduction -- 2 Methodology -- 2.1 Efficient Semantic Labeling with 3D FCN -- 2.2 Transfer Learning from C3D Model -- 2.3 Promote Training with Deep Supervision -- 2.4 Investigation of Class-Balanced Loss -- 3 Experimental Results -- 4 Conclusions -- References -- Automatic Segmentation of LV and RV in Cardiac MRI -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Dataset -- 2.2 Preprocessing -- 2.3 Architecture -- 3 Experimental Results -- 3.1 Implemented Details -- 3.2 Results and Quantitative Analysis with Other Methods -- 4 Conclusion and Discussion -- Acknowledgement -- References -- Automatic Multi-Atlas Segmentation of Myocardium with SVF-Net -- 1 Introduction -- 2 Rigid Alignment by Landmarks Detection -- 3 Non-rigid Diffeomorphic Registration with SVF-Net -- 4 Label Fusion Method -- 5 Results and Discussion -- 6 Conclusion -- References -- MM-WHS Challenge -- 3D Convolutional Networks for Fully Automatic Fine-Grained Whole Heart Partition -- 1 Introduction -- 2 Methodology -- 2.1 Dense Semantic Labeling with 3D FCN -- 2.2 Knowledge Transfer from C3D Model -- 2.3 Promote Training with Deep Supervision -- 2.4 Multi-class Balanced Loss Function -- 3 Experimental Results -- 4 Conclusions -- References -- Multi-label Whole Heart Segmentation Using CNNs and Anatomical Label Configurations -- 1 Introduction -- 2 Method -- 3 Experimental Setup -- 4 Results and Discussion -- 5 Conclusion -- References -- Multi-Planar Deep Segmentation Networks for Cardiac Substructures from MRI and CT -- 1 Introduction -- 2 Multi-Object Multi-Planar CNN (MO-MP-CNN) -- 3 Experimental Results -- 4 Discussion and Conclusion -- References -- Local Probabilistic Atlases and a Posteriori Correction for the Segmentation of Heart Images -- 1 Introduction -- 2 Methods. 2.1 Construction of the a Priori Information -- 2.2 Segmentation -- 2.3 A Posteriori Correction -- 3 Experiments -- 4 Results -- 5 Conclusion -- References -- Hybrid Loss Guided Convolutional Networks for Whole Heart Parsing -- 1 Introduction -- 2 Methodology -- 2.1 Intensity Calibration as Preprocessing -- 2.2 Enhance the Training of 3D FCN -- 2.3 Hybrid Loss Guided Class-Balanced Segmentation -- 3 Experimental Results -- 4 Conclusions -- References -- 3D Deeply-Supervised U-Net Based Whole Heart Segmentation -- 1 Introduction -- 2 Method -- 2.1 Data Pre-processing -- 2.2 Network Architecture -- 3 Experiments and Results -- 3.1 Data -- 3.2 Performance on Training Set -- 3.3 Performance on Testing Set -- 4 Discussion and Conclusion -- References -- MRI Whole Heart Segmentation Using Discrete Nonlinear Registration and Fast Non-local Fusion -- 1 Introduction and Related Work -- 2 Discrete Registration -- 3 Non-local Label Fusion -- 4 Multi-label Random Walk Regularisation -- 5 Discussion and Conclusion -- References -- Automatic Whole Heart Segmentation Using Deep Learning and Shape Context -- 1 Introduction -- 2 Methods -- 2.1 2.5D Segmentation Using Orthogonal U-Nets -- 2.2 Shape Context Generation -- 2.3 Shape-Context Guided U-Net -- 2.4 Implementation Details -- 3 Results -- 4 Discussion and Conclusion -- References -- Automatic Whole Heart Segmentation in CT Images Based on Multi-atlas Image Registration -- Abstract -- 1 Introduction -- 2 Methodology -- 2.1 A Three-Step Multi-atlas-Based Whole Heart Segmentation -- 2.2 Multiple Atlas Images -- 3 Experimental Results -- 4 Conclusion -- References -- Author Index. |
| Record Nr. | UNINA-9910349458403321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
L'énergie à découvert / / Rémy Mosseri, Catherine Jeandel
| L'énergie à découvert / / Rémy Mosseri, Catherine Jeandel |
| Autore | Alazard-Toux Nathalie |
| Pubbl/distr/stampa | Paris, : CNRS Éditions, 2017 |
| Descrizione fisica | 1 online resource (345 p.) |
| Altri autori (Persone) |
Alvarez-HéraultMarie-Cécile
ArnouxMathieu ArribartHervé ArteroVincent AverbuchDaniel BabaritAurélien BaraerFranck BéguinFrançois BelloubetNicole Beloin-Saint-PierreDidier BenvenisteAlbert BergelAlain BernardOlivier BessereauGeneviève BézianJean-Jacques BigotBernard BillebaudAnnick BlancIsabelle BlancPhilippe BoninBernard BoukhalfaMourad Abdelkrim BouneauSandra BraultPascal BréchetYves BrochonCyril BrosetaDaniel BrousseThierry CabarrocasPere Roca i CadoretJean-Paul CandelSébastien CarréFranck Cassier-ChauvatCorinne CathelineauMichel CauneauFrançois ChaudretBruno ChauvatFranck ChomazJean-Marc ChristmannPatrice CiaisPhilippe CloutetÉric ColombierMichel ColonnaPaul CornetJean-François CosnierSerge CriquiPatrick DandinPhilippe DavidSylvain DelmasClaude DementinSébastien DiazMichel DolletAlain DufrêcheJean-François DuplanJean-Luc DuroxDaniel DutoitThierry EspinarBella FavreÉric FéreyGérard FierobeHenri-Pierre FinonDominique FlamantGilles FleuryGuillaume FontecaveMarc FruchartDaniel FuchsAlain GabrielleBenoît GeantetChristophe GeoffronPatrice GiardDominique GloaguenFrédéric GobertJulie GofféBruno GökalpIskender GrambowBernd GuérinFrédéric GuiberteauPhilippe GuillaudXavier GuillemolesJean-François GuillouetStéphane GuyotFrançois HadjsaidNouredine HadziioannouGeorges HamelinJérôme HarauxFrancis HarocheSerge HennequinPascale HétreuxGilles HöfteHerman HossonCécile de HourcadeJean-Charles HucAlain-Yves JeandelCatherine JolyJean-Pierre JouveCarole Molina KalaydjianFrançois KergomardClaude KleiderJean-Paul KleinÉtienne KovacsFrancis KrobDaniel LabussièreOlivier LachalBernard LagabrielleYves LaraMichel De LassèguesPierre LatrilleÉric LaurentVictoire LédéJacques LégerChristophe LegrandJack LeroyMaurice LincotDaniel LojouElisabeth MarsilyGhislain de MassonRoland Masson-DelmotteValérie MayerDidier MéplanOlivier Merle-LucotteElsa MichelsRaymond MiquelJacques MoisanFrançois MontagneXavier MosseriRémy MousseauNormand NaghaviNegar NaourFrançois Le NatafHenri-Claude OdruPierre PaillardDidier PapillonPhilippe PeltierGilles PerceboisJacques Percheron-GuéganAnnick PerraudinÉmilie PiégayHervé Pijaudier-CabotGilles PoinssotChristophe PourcellyGérald PyXavier QuenardDaniel RablAri RaimondJean-Michel RaisonBertrand RappaportFabrice RavelFrédéric RenardFrançois ReussPaul RobertChristelle RotenbergBenjamin RoureFrançois RoussetMarc RutherfordJonathan SabonnadièreJean-Claude SanjuanBernard SchollhammerPhilippe SciandraAntoine SentieysOlivier SerçaDominique SerreChristian SimonChristian SimonPatrice SlaouiAbdelilah SonnendrückerÉric SteyerJean-Philippe TarasconJean-Marie TardieuBernard TheryRaphaële TissierMatthieu TixadorPascal TorréJean-Philippe TrablyÉric TreutHervé Le UribelarreaJean-Louis ValentinLuc VathaireFlorent de VernierRomain ViallyRoland VillenaveÉric ViolletPierre-Louis VrinatMichel WaldLucien WollmanFrancis-André YverCamille ZélemMarie-Christine ZissisGeorges |
| Collana | À découvert |
| Soggetto topico |
Environmental studies, Geography & Development
énergie environnement politique économie ressource naturelle |
| Soggetto non controllato |
énergie
environnement politique économie ressource naturelle |
| ISBN |
2-271-11914-6
2-271-07696-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Altri titoli varianti | ENERGIE A DECOUVERT |
| Record Nr. | UNINA-9910495833403321 |
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Alazard-Toux Nathalie
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| Paris, : CNRS Éditions, 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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