Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Fairness of AI in Medical Imaging : Third International Workshop, FAIMI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23, 2025, Proceedings
| Fairness of AI in Medical Imaging : Third International Workshop, FAIMI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23, 2025, Proceedings |
| Autore | Puyol-Antón Esther |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2025 |
| Descrizione fisica | 1 online resource (365 pages) |
| Disciplina | 616.0754 |
| Altri autori (Persone) |
FerranteEnzo
FeragenAasa KingAndrew CheplyginaVeronika Ganz-BenjaminsenMelani GlockerBen PetersenEike LeeHeisook |
| Collana | Lecture Notes in Computer Science Series |
| ISBN |
9783032058706
9783032058690 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996678669603316 |
Puyol-Antón Esther
|
||
| Cham : , : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Information processing in medical imaging : 27th International Conference, IPMI 2021, Virtual event, June 28-June 30, 2021, Proceedings / / Editor, Aasa Feragen [and three others]
| Information processing in medical imaging : 27th International Conference, IPMI 2021, Virtual event, June 28-June 30, 2021, Proceedings / / Editor, Aasa Feragen [and three others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (784 pages) |
| Disciplina | 006.6 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Diagnostic imaging - Data processing |
| ISBN | 3-030-78191-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Registration -- HyperMorph: Amortized Hyperparameter Learning for Image Registration -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 HyperMorph -- 3.2 Hyperparameter Tuning -- 3.3 Implementation -- 4 Experiments -- 4.1 Experiment 1: HyperMorph Efficiency and Capacity -- 4.2 Experiment 2: Robustness to Initialization -- 4.3 Experiment 3: Hyperparameter-Tuning Utility -- 5 Conclusion -- References -- Deep Learning Based Geometric Registration for Medical Images: How Accurate Can We Get Without Visual Features? -- 1 Introduction -- 1.1 Related Work -- 1.2 Contribution -- 2 Methods -- 2.1 Loopy Belief Propagation for Regularised Registration of Keypoint Graphs -- 2.2 Geometric Feature Extraction with Graph Convolutional Neural Networks -- 2.3 Deep Learning Based End-to-End Geometric Registration Framework -- 2.4 Implementation Details: Keypoints, Visual Features and Integral Loss -- 3 Experiments and Results -- 4 Discussion and Conclusion -- References -- Diffeomorphic Registration with Density Changes for the Analysis of Imbalanced Shapes -- 1 Introduction -- 2 Diffeomorphic Registration of Geometric Measures -- 2.1 Diffeomorphisms and Registration -- 2.2 Geometric Measure Representation of Shapes -- 3 Diffeomorphic Registration with Density Changes -- 3.1 An Augmented Optimal Control Problem -- 3.2 Numerical Implementation -- 3.3 Local Density Changes -- 4 Results -- 5 Conclusion -- References -- Causal Models and Interpretability -- Estimation of Causal Effects in the Presence of Unobserved Confounding in the Alzheimer's Continuum -- 1 Introduction -- 2 Methods -- 2.1 The Causal Question and Its Associated Graph -- 2.2 Identifiability in the Presence of an Unobserved Confounder -- 2.3 Estimating a Substitute Confounder -- 2.4 Identifiability in the Presence of a Substitute Confounder.
2.5 The Outcome Model -- 3 Experiments -- 4 Conclusion -- References -- Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal Modeling -- 1 Introduction -- 2 Methods -- 2.1 Notations and Formulation of Problem -- 2.2 Multiple-Shooting Method -- 2.3 Adjoint State Method -- 2.4 Multiple-Shooting Adjoint (MSA) Method -- 2.5 Dynamic Causal Modeling -- 3 Experiments -- 3.1 Validation on Toy Examples -- 3.2 Application to Whole-Brain Dynamic Causal Modeling with fMRI -- 4 Conclusion -- References -- Going Beyond Saliency Maps: Training Deep Models to Interpret Deep Models -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Cycle-Consistent Image Simulation -- 3.2 Coupling Simulators via Conditional Convolution -- 3.3 Learning Warping Fields -- 4 Experiments -- 4.1 Synthetic Experiments -- 4.2 Visualizing the Effect of Alzheimer's Disease -- 4.3 Visualizing the Effect of Alcohol Dependence -- 5 Conclusion -- References -- Generative Modelling -- Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Preliminaries -- 3.2 Regularized Adversarial Data Augmentation -- 3.3 Data Augmentation Space and Models -- 4 Experiments -- 4.1 Experiments Setup -- 4.2 Skin Lesion Diagnosis Result -- 4.3 Organ-at-Risk Segmentation Result -- 5 Conclusion -- References -- Blind Stain Separation Using Model-Aware Generative Learning and Its Applications on Fluorescence Microscopy Images -- 1 Introduction -- 2 Methodology -- 3 Fluorescence Unmixing -- 4 Experimental Evaluation -- 4.1 Experimental Setup -- 4.2 Results and Discussions -- 5 Conclusions -- References -- MR Slice Profile Estimation by Learning to Match Internal Patch Distributions -- 1 Introduction -- 2 Methods -- 2.1 Slice Profile -- 2.2 Slice Profile and Internal Patch Distributions. 2.3 Slice Profile and GAN -- 2.4 Regularization Functions and Other Details -- 3 Experiments and Results -- 3.1 Simulations from Isotropic Images -- 3.2 Incorporating Slice Profile Estimation into SMORE -- 3.3 Measuring Through-Plane Resolution After Applying SMORE -- 4 Discussion and Conclusions -- References -- Shape -- Partial Matching in the Space of Varifolds -- 1 Introduction -- 2 Partial Matching -- 2.1 The Varifold Framework for Shape Matching -- 2.2 Definition of the Partial Matching Dissimilarity -- 2.3 Normalized Partial Matching Dissimilarity -- 2.4 Use in the LDDMM Setting -- 3 Experiments -- 4 Conclusion -- References -- Nested Grassmanns for Dimensionality Reduction with Applications to Shape Analysis -- 1 Introduction -- 2 Nested Grassmannians -- 2.1 The Riemannian Geometry of Grassmann Manifolds -- 2.2 Embedding of Gr(p, m) in Gr(p, n) -- 2.3 Unsupervised Dimensionality Reduction -- 2.4 Supervised Dimensionality Reduction -- 2.5 Choice of the Distance d -- 2.6 Analysis of Principal Nested Grassmanns -- 3 Experiments -- 3.1 Synthetic Data -- 3.2 Application to Planar Shape Analysis -- 4 Conclusion -- References -- Hierarchical Morphology-Guided Tooth Instance Segmentation from CBCT Images -- 1 Introduction -- 2 Methods -- 2.1 Tooth Centroid and Skeleton Extraction Network -- 2.2 Multi-task Learning for Tooth Segmentation -- 2.3 Implementation Details -- 3 Experimental Results -- 3.1 Dataset and Evaluation Metrics -- 3.2 Evaluation and Comparison -- 3.3 Comparison with the State-of-the-Art Methods -- 4 Conclusion -- References -- Cortical Morphometry Analysis Based on Worst Transportation Theory -- 1 Introduction -- 2 Theoretic Results -- 2.1 Optimal Transportation Map -- 2.2 Worst Transportation Map -- 2.3 Geometric Variational Method -- 3 Computational Algorithms -- 3.1 Basic Concepts from Computational Geometry. 3.2 Algorithms Based on Computational Geometry -- 4 Experiments -- 5 Conclusion -- References -- Geodesic B-score for Improved Assessment of Knee Osteoarthritis -- 1 Introduction -- 2 Background -- 2.1 Shape Space -- 2.2 Geometric Statistics -- 3 Geodesic B-score -- 3.1 Generalization -- 3.2 Sex-Specific Reference -- 3.3 Algorithmic Treatment -- 4 Results and Discussion -- 4.1 Data Description -- 4.2 Efficiency of Projection Algorithm -- 4.3 Predictive Validity -- 5 Conclusion and Future Work -- References -- Brain Connectivity -- Cytoarchitecture Measurements in Brain Gray Matter Using Likelihood-Free Inference -- 1 Introduction -- 2 Methods -- 2.1 Modeling the Brain Gray Matter with a 3-Compartment Model -- 2.2 An Invertible 3-Compartment Model: dMRI Summary Statistics -- 2.3 Solving the Inverse Problem via Likelihood Free Inference -- 3 Results and Discussion -- 3.1 Simulations -- 3.2 HCP MGH Results -- 4 Conclusion -- References -- Non-isomorphic Inter-modality Graph Alignment and Synthesis for Holistic Brain Mapping -- 1 Introduction -- 2 Methodology -- 3 Experimental Results and Discussion -- 4 Conclusion -- References -- Knowledge Transfer for Few-Shot Segmentation of Novel White Matter Tracts -- 1 Introduction -- 2 Methods -- 2.1 Problem Formulation and Classic Fine-Tuning -- 2.2 Knowledge Transfer for Few-Shot Segmentation of Novel WM Tracts -- 2.3 A Better Implementation with Warmup -- 2.4 Implementation Details -- 3 Results -- 3.1 Data Description and Experimental Settings -- 3.2 Evaluation of Segmentation Accuracy -- 3.3 Impact of the Number of Annotated Training Scans -- 3.4 Evaluation of Volume Difference -- 4 Discussion -- 5 Conclusion -- References -- Discovering Spreading Pathways of Neuropathological Events in Alzheimer's Disease Using Harmonic Wavelets -- 1 Introduction -- 2 Methods -- 2.1 Manifold Harmonics. 2.2 Construction of Region-Adaptive Harmonic Wavelets -- 3 Experiments -- 3.1 Evaluate the Representation Power on Harmonic Wavelets -- 3.2 Evaluate the Statistic Power of Harmonic Wavelet Fingerprint -- 4 Conclusions -- References -- A Multi-scale Spatial and Temporal Attention Network on Dynamic Connectivity to Localize the Eloquent Cortex in Brain Tumor Patients -- 1 Introduction -- 2 A Multi-scale Spatial and Temporal Attention Network to Localize the Eloquent Cortex -- 2.1 Input Dynamic Connectivity Matrices -- 2.2 Multi-scale Spatial Attention on Convolutional Features -- 2.3 Temporal Attention Model and Multi-task Learning -- 3 Experimental Results -- 3.1 Dataset and Preprocessing -- 3.2 Localization Results -- 3.3 Feature Analysis -- 4 Conclusion -- References -- Learning Multi-resolution Graph Edge Embedding for Discovering Brain Network Dysfunction in Neurological Disorders -- 1 Introduction -- 1.1 Related Work -- 2 Proposed Method -- 2.1 Multi-resolution Graph Edge Transform -- 2.2 Efficient Graph Matrix Transform -- 2.3 Network Architecture -- 2.4 Training MENET -- 3 Experiments -- 3.1 Datasets -- 3.2 Experimental Settings -- 3.3 Structural Brain Connectivity Analysis on ADNI -- 3.4 Functional Brain Connectivity Analysis on ADHD -- 3.5 Discussions on Convergence of Scales -- 4 Conclusion -- References -- Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data -- 1 Introduction -- 2 Methods -- 2.1 Background and Preliminaries -- 2.2 Equivariant Spherical Deconvolution -- 3 Experiments -- 3.1 Noisy Synthetic Benchmark -- 3.2 The Tractometer Benchmark -- 3.3 Real-World Multi-shell Human Dataset -- 4 Discussion -- References -- Geodesic Tubes for Uncertainty Quantification in Diffusion MRI -- 1 Introduction -- 2 Theory -- 3 Experiments -- 4 Discussion -- References. Structural Connectome Atlas Construction in the Space of Riemannian Metrics. |
| Record Nr. | UNISA-996464490903316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Information processing in medical imaging : 27th International Conference, IPMI 2021, Virtual event, June 28-June 30, 2021, Proceedings / / Editor, Aasa Feragen [and three others]
| Information processing in medical imaging : 27th International Conference, IPMI 2021, Virtual event, June 28-June 30, 2021, Proceedings / / Editor, Aasa Feragen [and three others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (784 pages) |
| Disciplina | 006.6 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Diagnostic imaging - Data processing |
| ISBN | 3-030-78191-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Registration -- HyperMorph: Amortized Hyperparameter Learning for Image Registration -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 HyperMorph -- 3.2 Hyperparameter Tuning -- 3.3 Implementation -- 4 Experiments -- 4.1 Experiment 1: HyperMorph Efficiency and Capacity -- 4.2 Experiment 2: Robustness to Initialization -- 4.3 Experiment 3: Hyperparameter-Tuning Utility -- 5 Conclusion -- References -- Deep Learning Based Geometric Registration for Medical Images: How Accurate Can We Get Without Visual Features? -- 1 Introduction -- 1.1 Related Work -- 1.2 Contribution -- 2 Methods -- 2.1 Loopy Belief Propagation for Regularised Registration of Keypoint Graphs -- 2.2 Geometric Feature Extraction with Graph Convolutional Neural Networks -- 2.3 Deep Learning Based End-to-End Geometric Registration Framework -- 2.4 Implementation Details: Keypoints, Visual Features and Integral Loss -- 3 Experiments and Results -- 4 Discussion and Conclusion -- References -- Diffeomorphic Registration with Density Changes for the Analysis of Imbalanced Shapes -- 1 Introduction -- 2 Diffeomorphic Registration of Geometric Measures -- 2.1 Diffeomorphisms and Registration -- 2.2 Geometric Measure Representation of Shapes -- 3 Diffeomorphic Registration with Density Changes -- 3.1 An Augmented Optimal Control Problem -- 3.2 Numerical Implementation -- 3.3 Local Density Changes -- 4 Results -- 5 Conclusion -- References -- Causal Models and Interpretability -- Estimation of Causal Effects in the Presence of Unobserved Confounding in the Alzheimer's Continuum -- 1 Introduction -- 2 Methods -- 2.1 The Causal Question and Its Associated Graph -- 2.2 Identifiability in the Presence of an Unobserved Confounder -- 2.3 Estimating a Substitute Confounder -- 2.4 Identifiability in the Presence of a Substitute Confounder.
2.5 The Outcome Model -- 3 Experiments -- 4 Conclusion -- References -- Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal Modeling -- 1 Introduction -- 2 Methods -- 2.1 Notations and Formulation of Problem -- 2.2 Multiple-Shooting Method -- 2.3 Adjoint State Method -- 2.4 Multiple-Shooting Adjoint (MSA) Method -- 2.5 Dynamic Causal Modeling -- 3 Experiments -- 3.1 Validation on Toy Examples -- 3.2 Application to Whole-Brain Dynamic Causal Modeling with fMRI -- 4 Conclusion -- References -- Going Beyond Saliency Maps: Training Deep Models to Interpret Deep Models -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Cycle-Consistent Image Simulation -- 3.2 Coupling Simulators via Conditional Convolution -- 3.3 Learning Warping Fields -- 4 Experiments -- 4.1 Synthetic Experiments -- 4.2 Visualizing the Effect of Alzheimer's Disease -- 4.3 Visualizing the Effect of Alcohol Dependence -- 5 Conclusion -- References -- Generative Modelling -- Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Preliminaries -- 3.2 Regularized Adversarial Data Augmentation -- 3.3 Data Augmentation Space and Models -- 4 Experiments -- 4.1 Experiments Setup -- 4.2 Skin Lesion Diagnosis Result -- 4.3 Organ-at-Risk Segmentation Result -- 5 Conclusion -- References -- Blind Stain Separation Using Model-Aware Generative Learning and Its Applications on Fluorescence Microscopy Images -- 1 Introduction -- 2 Methodology -- 3 Fluorescence Unmixing -- 4 Experimental Evaluation -- 4.1 Experimental Setup -- 4.2 Results and Discussions -- 5 Conclusions -- References -- MR Slice Profile Estimation by Learning to Match Internal Patch Distributions -- 1 Introduction -- 2 Methods -- 2.1 Slice Profile -- 2.2 Slice Profile and Internal Patch Distributions. 2.3 Slice Profile and GAN -- 2.4 Regularization Functions and Other Details -- 3 Experiments and Results -- 3.1 Simulations from Isotropic Images -- 3.2 Incorporating Slice Profile Estimation into SMORE -- 3.3 Measuring Through-Plane Resolution After Applying SMORE -- 4 Discussion and Conclusions -- References -- Shape -- Partial Matching in the Space of Varifolds -- 1 Introduction -- 2 Partial Matching -- 2.1 The Varifold Framework for Shape Matching -- 2.2 Definition of the Partial Matching Dissimilarity -- 2.3 Normalized Partial Matching Dissimilarity -- 2.4 Use in the LDDMM Setting -- 3 Experiments -- 4 Conclusion -- References -- Nested Grassmanns for Dimensionality Reduction with Applications to Shape Analysis -- 1 Introduction -- 2 Nested Grassmannians -- 2.1 The Riemannian Geometry of Grassmann Manifolds -- 2.2 Embedding of Gr(p, m) in Gr(p, n) -- 2.3 Unsupervised Dimensionality Reduction -- 2.4 Supervised Dimensionality Reduction -- 2.5 Choice of the Distance d -- 2.6 Analysis of Principal Nested Grassmanns -- 3 Experiments -- 3.1 Synthetic Data -- 3.2 Application to Planar Shape Analysis -- 4 Conclusion -- References -- Hierarchical Morphology-Guided Tooth Instance Segmentation from CBCT Images -- 1 Introduction -- 2 Methods -- 2.1 Tooth Centroid and Skeleton Extraction Network -- 2.2 Multi-task Learning for Tooth Segmentation -- 2.3 Implementation Details -- 3 Experimental Results -- 3.1 Dataset and Evaluation Metrics -- 3.2 Evaluation and Comparison -- 3.3 Comparison with the State-of-the-Art Methods -- 4 Conclusion -- References -- Cortical Morphometry Analysis Based on Worst Transportation Theory -- 1 Introduction -- 2 Theoretic Results -- 2.1 Optimal Transportation Map -- 2.2 Worst Transportation Map -- 2.3 Geometric Variational Method -- 3 Computational Algorithms -- 3.1 Basic Concepts from Computational Geometry. 3.2 Algorithms Based on Computational Geometry -- 4 Experiments -- 5 Conclusion -- References -- Geodesic B-score for Improved Assessment of Knee Osteoarthritis -- 1 Introduction -- 2 Background -- 2.1 Shape Space -- 2.2 Geometric Statistics -- 3 Geodesic B-score -- 3.1 Generalization -- 3.2 Sex-Specific Reference -- 3.3 Algorithmic Treatment -- 4 Results and Discussion -- 4.1 Data Description -- 4.2 Efficiency of Projection Algorithm -- 4.3 Predictive Validity -- 5 Conclusion and Future Work -- References -- Brain Connectivity -- Cytoarchitecture Measurements in Brain Gray Matter Using Likelihood-Free Inference -- 1 Introduction -- 2 Methods -- 2.1 Modeling the Brain Gray Matter with a 3-Compartment Model -- 2.2 An Invertible 3-Compartment Model: dMRI Summary Statistics -- 2.3 Solving the Inverse Problem via Likelihood Free Inference -- 3 Results and Discussion -- 3.1 Simulations -- 3.2 HCP MGH Results -- 4 Conclusion -- References -- Non-isomorphic Inter-modality Graph Alignment and Synthesis for Holistic Brain Mapping -- 1 Introduction -- 2 Methodology -- 3 Experimental Results and Discussion -- 4 Conclusion -- References -- Knowledge Transfer for Few-Shot Segmentation of Novel White Matter Tracts -- 1 Introduction -- 2 Methods -- 2.1 Problem Formulation and Classic Fine-Tuning -- 2.2 Knowledge Transfer for Few-Shot Segmentation of Novel WM Tracts -- 2.3 A Better Implementation with Warmup -- 2.4 Implementation Details -- 3 Results -- 3.1 Data Description and Experimental Settings -- 3.2 Evaluation of Segmentation Accuracy -- 3.3 Impact of the Number of Annotated Training Scans -- 3.4 Evaluation of Volume Difference -- 4 Discussion -- 5 Conclusion -- References -- Discovering Spreading Pathways of Neuropathological Events in Alzheimer's Disease Using Harmonic Wavelets -- 1 Introduction -- 2 Methods -- 2.1 Manifold Harmonics. 2.2 Construction of Region-Adaptive Harmonic Wavelets -- 3 Experiments -- 3.1 Evaluate the Representation Power on Harmonic Wavelets -- 3.2 Evaluate the Statistic Power of Harmonic Wavelet Fingerprint -- 4 Conclusions -- References -- A Multi-scale Spatial and Temporal Attention Network on Dynamic Connectivity to Localize the Eloquent Cortex in Brain Tumor Patients -- 1 Introduction -- 2 A Multi-scale Spatial and Temporal Attention Network to Localize the Eloquent Cortex -- 2.1 Input Dynamic Connectivity Matrices -- 2.2 Multi-scale Spatial Attention on Convolutional Features -- 2.3 Temporal Attention Model and Multi-task Learning -- 3 Experimental Results -- 3.1 Dataset and Preprocessing -- 3.2 Localization Results -- 3.3 Feature Analysis -- 4 Conclusion -- References -- Learning Multi-resolution Graph Edge Embedding for Discovering Brain Network Dysfunction in Neurological Disorders -- 1 Introduction -- 1.1 Related Work -- 2 Proposed Method -- 2.1 Multi-resolution Graph Edge Transform -- 2.2 Efficient Graph Matrix Transform -- 2.3 Network Architecture -- 2.4 Training MENET -- 3 Experiments -- 3.1 Datasets -- 3.2 Experimental Settings -- 3.3 Structural Brain Connectivity Analysis on ADNI -- 3.4 Functional Brain Connectivity Analysis on ADHD -- 3.5 Discussions on Convergence of Scales -- 4 Conclusion -- References -- Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data -- 1 Introduction -- 2 Methods -- 2.1 Background and Preliminaries -- 2.2 Equivariant Spherical Deconvolution -- 3 Experiments -- 3.1 Noisy Synthetic Benchmark -- 3.2 The Tractometer Benchmark -- 3.3 Real-World Multi-shell Human Dataset -- 4 Discussion -- References -- Geodesic Tubes for Uncertainty Quantification in Diffusion MRI -- 1 Introduction -- 2 Theory -- 3 Experiments -- 4 Discussion -- References. Structural Connectome Atlas Construction in the Space of Riemannian Metrics. |
| Record Nr. | UNINA-9910485594103321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part III / / edited by Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part III / / edited by Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel |
| Autore | Linguraru Marius George |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (827 pages) |
| Disciplina | 006 |
| Altri autori (Persone) |
DouQi
FeragenAasa GiannarouStamatia GlockerBen LekadirKarim SchnabelJulia A |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Application software Machine learning Education - Data processing Social sciences - Data processing Biomedical engineering Computer Imaging, Vision, Pattern Recognition and Graphics Computer and Information Systems Applications Machine Learning Computers and Education Computer Application in Social and Behavioral Sciences Biomedical Engineering and Bioengineering |
| ISBN | 3-031-72384-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910896179503321 |
|
Linguraru Marius George
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part VIII / / edited by Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part VIII / / edited by Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel |
| Autore | Linguraru Marius George |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (802 pages) |
| Disciplina | 006 |
| Altri autori (Persone) |
DouQi
FeragenAasa GiannarouStamatia GlockerBen LekadirKarim SchnabelJulia A |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Application software Machine learning Education - Data processing Social sciences - Data processing Biomedical engineering Computer Imaging, Vision, Pattern Recognition and Graphics Computer and Information Systems Applications Machine Learning Computers and Education Computer Application in Social and Behavioral Sciences Biomedical Engineering and Bioengineering |
| ISBN | 3-031-72111-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910896183703321 |
|
Linguraru Marius George
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part I / / edited by Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part I / / edited by Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel |
| Autore | Linguraru Marius George |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (823 pages) |
| Disciplina | 006 |
| Altri autori (Persone) |
DouQi
FeragenAasa GiannarouStamatia GlockerBen LekadirKarim SchnabelJulia A |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Application software Machine learning Education - Data processing Social sciences - Data processing Biomedical engineering Computer Imaging, Vision, Pattern Recognition and Graphics Computer and Information Systems Applications Machine Learning Computers and Education Computer Application in Social and Behavioral Sciences Biomedical Engineering and Bioengineering |
| ISBN | 3-031-72378-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910896182703321 |
|
Linguraru Marius George
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part II / / edited by Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part II / / edited by Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel |
| Autore | Linguraru Marius George |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (819 pages) |
| Disciplina | 006 |
| Altri autori (Persone) |
DouQi
FeragenAasa GiannarouStamatia GlockerBen LekadirKarim SchnabelJulia A |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Application software Machine learning Education - Data processing Social sciences - Data processing Biomedical engineering Computer Imaging, Vision, Pattern Recognition and Graphics Computer and Information Systems Applications Machine Learning Computers and Education Computer Application in Social and Behavioral Sciences Biomedical Engineering and Bioengineering |
| ISBN | 3-031-72069-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910896183203321 |
|
Linguraru Marius George
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part IX / / edited by Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part IX / / edited by Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel |
| Autore | Linguraru Marius George |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (782 pages) |
| Disciplina | 006 |
| Altri autori (Persone) |
DouQi
FeragenAasa GiannarouStamatia GlockerBen LekadirKarim SchnabelJulia A |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Application software Machine learning Education - Data processing Social sciences - Data processing Biomedical engineering Computer Imaging, Vision, Pattern Recognition and Graphics Computer and Information Systems Applications Machine Learning Computers and Education Computer Application in Social and Behavioral Sciences Biomedical Engineering and Bioengineering |
| ISBN | 3-031-72114-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910896192803321 |
|
Linguraru Marius George
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part V / / edited by Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part V / / edited by Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel |
| Autore | Linguraru Marius George |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (815 pages) |
| Disciplina | 006 |
| Altri autori (Persone) |
DouQi
FeragenAasa GiannarouStamatia GlockerBen LekadirKarim SchnabelJulia A |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Application software Machine learning Education - Data processing Social sciences - Data processing Biomedical engineering Computer Imaging, Vision, Pattern Recognition and Graphics Computer and Information Systems Applications Machine Learning Computers and Education Computer Application in Social and Behavioral Sciences Biomedical Engineering and Bioengineering |
| ISBN | 3-031-72086-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910896185503321 |
|
Linguraru Marius George
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part X / / edited by Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part X / / edited by Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel |
| Autore | Linguraru Marius George |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (807 pages) |
| Disciplina | 006 |
| Altri autori (Persone) |
DouQi
FeragenAasa GiannarouStamatia GlockerBen LekadirKarim SchnabelJulia A |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Application software Machine learning Education - Data processing Social sciences - Data processing Biomedical engineering Computer Imaging, Vision, Pattern Recognition and Graphics Computer and Information Systems Applications Machine Learning Computers and Education Computer Application in Social and Behavioral Sciences Biomedical Engineering and Bioengineering |
| ISBN | 3-031-72117-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910896187703321 |
|
Linguraru Marius George
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
