Biomedical Image Registration [[electronic resource] ] : 9th International Workshop, WBIR 2020, Portorož, Slovenia, December 1–2, 2020, Proceedings / / edited by Žiga Špiclin, Jamie McClelland, Jan Kybic, Orcun Goksel |
Edizione | [1st ed. 2020.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
Descrizione fisica | 1 online resource (x, 176 pages) : illustrations |
Disciplina | 616.0754 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Artificial intelligence Pattern recognition Application software Computer organization Computers Image Processing and Computer Vision Artificial Intelligence Pattern Recognition Computer Applications Computer Systems Organization and Communication Networks Computing Milieux |
ISBN | 3-030-50120-5 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Registration Initialization and Acceleration -- Nonlinear Alignment of Whole Tractograms with the Linear Assignment Problem -- Learning-based Affine Registration of Histological Images -- Enabling Manual Intervention for Otherwise Automated Registration of Large Image Series -- Towards Segmentation and Spatial Alignment of the Human Embryonic Brain using Deep Learning for Atlas-based Registration -- Learning Deformable Image Registration with Structure Guidance Constraints for Adaptive Radiotherapy -- Interventional Registration -- Multilevel 2D-3D Intensity-based Image Registration -- Towards Automated Spine Mobility Quantification: a Locally Rigid CT to X-ray Registration Framework -- Landmark based Registration -- Reinforced Redetection of Landmark in Pre- and Post-Operative Brain Scan using Anatomical Guidance for Image Alignment -- Deep Volumetric Feature Encoding for Biomedical Images -- Multi-Channel Registration -- Multi-Channel Image Registration of Cardiac MR Using Supervised Feature Learning with Convolutional Encoder-Decoder Network -- Multi-Channel Registration for Diffusion MRI: Longitudinal Analysis for the Neonatal Brain -- An Image Registration-based Method for EPI Distortion Correction based on Opposite Phase Encoding (COPE) -- Diffusion Tensor driven Image registration: a Deep Learning Approach -- Multimodal MRI Template Creation in the Ring-Tailed Lemur and Rhesus Macaque -- Sliding Motion -- An Unsupervised Learning Approach to Discontinuity-preserving Image Registration -- An Image Registration Framework for Discontinuous Mappings along Cracks. |
Record Nr. | UNISA-996418311703316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Biomedical Image Registration : 9th International Workshop, WBIR 2020, Portorož, Slovenia, December 1–2, 2020, Proceedings / / edited by Žiga Špiclin, Jamie McClelland, Jan Kybic, Orcun Goksel |
Edizione | [1st ed. 2020.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
Descrizione fisica | 1 online resource (x, 176 pages) : illustrations |
Disciplina |
616.0754
006.6 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Artificial intelligence Pattern recognition Application software Computer organization Computers Image Processing and Computer Vision Artificial Intelligence Pattern Recognition Computer Applications Computer Systems Organization and Communication Networks Computing Milieux |
ISBN | 3-030-50120-5 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Registration Initialization and Acceleration -- Nonlinear Alignment of Whole Tractograms with the Linear Assignment Problem -- Learning-based Affine Registration of Histological Images -- Enabling Manual Intervention for Otherwise Automated Registration of Large Image Series -- Towards Segmentation and Spatial Alignment of the Human Embryonic Brain using Deep Learning for Atlas-based Registration -- Learning Deformable Image Registration with Structure Guidance Constraints for Adaptive Radiotherapy -- Interventional Registration -- Multilevel 2D-3D Intensity-based Image Registration -- Towards Automated Spine Mobility Quantification: a Locally Rigid CT to X-ray Registration Framework -- Landmark based Registration -- Reinforced Redetection of Landmark in Pre- and Post-Operative Brain Scan using Anatomical Guidance for Image Alignment -- Deep Volumetric Feature Encoding for Biomedical Images -- Multi-Channel Registration -- Multi-Channel Image Registration of Cardiac MR Using Supervised Feature Learning with Convolutional Encoder-Decoder Network -- Multi-Channel Registration for Diffusion MRI: Longitudinal Analysis for the Neonatal Brain -- An Image Registration-based Method for EPI Distortion Correction based on Opposite Phase Encoding (COPE) -- Diffusion Tensor driven Image registration: a Deep Learning Approach -- Multimodal MRI Template Creation in the Ring-Tailed Lemur and Rhesus Macaque -- Sliding Motion -- An Unsupervised Learning Approach to Discontinuity-preserving Image Registration -- An Image Registration Framework for Discontinuous Mappings along Cracks. |
Record Nr. | UNINA-9910410059703321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Simulation and Synthesis in Medical Imaging [[electronic resource] ] : Third International Workshop, SASHIMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings / / edited by Ali Gooya, Orcun Goksel, Ipek Oguz, Ninon Burgos |
Edizione | [1st ed. 2018.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
Descrizione fisica | 1 online resource (X, 140 p. 58 illus.) |
Disciplina | 616.07540285 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Health informatics Artificial intelligence Computer security Image Processing and Computer Vision Health Informatics Artificial Intelligence Systems and Data Security |
ISBN | 3-030-00536-4 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Medical Image Synthesis for Data Augmentation and Anonymization Using Generative Adversarial Networks -- Data Augmentation Using synthetic Lesions Improves Machine Learning Detection of Microbleeds from MRI -- Deep Harmonization of Inconsistent MR Data for Consistent Volume Segmentation -- Cross-modality Image Synthesis from Unpaired Data Using CycleGAN: Effects of Gradient Consistency Loss and Training Data Size -- A Machine Learning Approach to Diffusion MRI Partial Volume Estimation -- Unsupervised Learning for Cross-domain Medical Image Synthesis Using Deformation Invariant Cycle Consistency Networks -- Deep Boosted Regression for MR TO CT Synthesis -- Model-Based Generation of Synthetic 3D Time-Lapse Sequences of Multiple Mutually Interacting Motile Cells with Filopodia -- MRI to FDG-PET: Cross-Modal Synthesis Using 3D U-Net for Multi-Modal Alzheimer’s Classification -- Tubular Network Formation Process Using 3D Cellular Potts Model -- Deep Learning Based Coronary Artery Motion Artifact Compensation Using Style-Transfer Synthesis in CT Images -- Lung Nodule Synthesis Using CNN-based Latent Data Representation -- RS-Net: Regression-Segmentation 3D CNN for Synthesis of Full Resolution Missing Brain MRI in the Presence of Tumours -- Generating Magnetic Resonance Spectroscopy Imaging Data of Brain Tumours from Linear, Non-Linear and Deep Learning Models. . |
Record Nr. | UNISA-996466214803316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Simulation and Synthesis in Medical Imaging : Third International Workshop, SASHIMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings / / edited by Ali Gooya, Orcun Goksel, Ipek Oguz, Ninon Burgos |
Edizione | [1st ed. 2018.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
Descrizione fisica | 1 online resource (X, 140 p. 58 illus.) |
Disciplina |
616.07540285
006.6 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Health informatics Artificial intelligence Computer security Image Processing and Computer Vision Health Informatics Artificial Intelligence Systems and Data Security |
ISBN | 3-030-00536-4 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Medical Image Synthesis for Data Augmentation and Anonymization Using Generative Adversarial Networks -- Data Augmentation Using synthetic Lesions Improves Machine Learning Detection of Microbleeds from MRI -- Deep Harmonization of Inconsistent MR Data for Consistent Volume Segmentation -- Cross-modality Image Synthesis from Unpaired Data Using CycleGAN: Effects of Gradient Consistency Loss and Training Data Size -- A Machine Learning Approach to Diffusion MRI Partial Volume Estimation -- Unsupervised Learning for Cross-domain Medical Image Synthesis Using Deformation Invariant Cycle Consistency Networks -- Deep Boosted Regression for MR TO CT Synthesis -- Model-Based Generation of Synthetic 3D Time-Lapse Sequences of Multiple Mutually Interacting Motile Cells with Filopodia -- MRI to FDG-PET: Cross-Modal Synthesis Using 3D U-Net for Multi-Modal Alzheimer’s Classification -- Tubular Network Formation Process Using 3D Cellular Potts Model -- Deep Learning Based Coronary Artery Motion Artifact Compensation Using Style-Transfer Synthesis in CT Images -- Lung Nodule Synthesis Using CNN-based Latent Data Representation -- RS-Net: Regression-Segmentation 3D CNN for Synthesis of Full Resolution Missing Brain MRI in the Presence of Tumours -- Generating Magnetic Resonance Spectroscopy Imaging Data of Brain Tumours from Linear, Non-Linear and Deep Learning Models. . |
Record Nr. | UNINA-9910349406303321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|