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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
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
Opac: Controlla la disponibilità qui
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
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
Opac: Controlla la disponibilità qui
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
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
Opac: Controlla la disponibilità qui
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
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
Opac: Controlla la disponibilità qui