Image Analysis for Moving Organ, Breast, and Thoracic Images [[electronic resource] ] : Third International Workshop, RAMBO 2018, Fourth International Workshop, BIA 2018, and First International Workshop, TIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16 and 20, 2018, Proceedings / / edited by Danail Stoyanov, Zeike Taylor, Bernhard Kainz, Gabriel Maicas, Reinhard R. Beichel, Anne Martel, Lena Maier-Hein, Kanwal Bhatia, Tom Vercauteren, Ozan Oktay, Gustavo Carneiro, Andrew P. Bradley, Jacinto Nascimento, Hang Min, Matthew S. Brown, Colin Jacobs, Bianca Lassen-Schmidt, Kensaku Mori, Jens Petersen, Raúl San José Estépar, Alexander Schmidt-Richberg, Catarina Veiga |
Edizione | [1st ed. 2018.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
Descrizione fisica | 1 online resource (xiv, 350 pages) : illustrations (chiefly color) |
Disciplina | 616.0754 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Artificial intelligence Health informatics Computers Image Processing and Computer Vision Artificial Intelligence Health Informatics Information Systems and Communication Service |
ISBN | 3-030-00946-7 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Resection-based Demons Regularization for Breast Tumor Bed Propagation -- Linear and Deformable Image Registration with 3D Convolutional Neural Networks -- Super Resolution of Cardiac Cine MRI Sequences Using Deep Learning -- Automated CNN-based Reconstruction of Short-Axis Cardiac MR Sequence From Real-Time Image Data -- An Unbiased Groupwise Registration Algorithm for Correcting Motion in Dynamic Contrast-Enhanced Magnetic Resonance Images -- Siamese Network for Dual-View Mammography Mass Matching -- Large-scale Mammography CAD with Deformable Conv-Nets -- Domain Adaptation for Deviating Acquisition Protocols in CNN-based Lesion Classification on Diffusion-Weighted MR Images -- Improved Breast Mass Segmentation in Mammograms with Conditional Residual U-net -- Improving Breast Cancer Detection using Symmetry Information -- Conditional Infilling GANs for Data Augmentation in Mammogram Classification -- A Unified Mammogram Analysis Method via Hybrid Deep Supervision -- Structure-aware Staging for Breast Cancer Metastases -- Reproducible evaluation of registration algorithms for movement correction in dynamic contrast enhancing magnetic resonance imaging for breast cancer diagnosis -- Robust Windowed Harmonic Phase Analysis with a Single Acquisition -- Lung Structures Enhancement in Chest Radiographs via CT based FCNN Training -- Improving the Segmentation of Anatomical Structures in Chest Radiographs using U-Net with an ImageNet Pre-trained Encoder -- Tuberculosis histopathology on x-ray CT -- A CT scan harmonization technique to detect Emphysema and Small Airway Diseases -- Transfer Learning for Segmentation of Injured Lungs using Coarse-to-Fine Convolutional Neural Networks -- High throughput lung and lobar segmentation by 2D and 3D CNN on chest CT with diffuse lung disease -- Multi-Structure Segmentation from Partially Labeled Datasets. Application to Body Composition Measurements on CT scans -- 3D Pulmonary Artery Segmentation from CTA Scans using Deep Learning with Realistic Data Augmentation -- Automatic Airway Segmentation in chest CT using Convolutional Neural Networks -- Detecting Out-of-phase Ventilation Using 4DCT to Improve Radiation Therapy for Lung Cancer -- XeMRI to CT Lung Image Registration Enhanced with Personalized 4DCT-derived Motion Model -- Rigid Lens – Locally Rigid Approximations of Deformable Registration for Change Assessment in Thorax-Abdomen CT Follow-Up Scan -- Diffeomorphic Lung Registration using Deep CNNs and Reinforced Learning -- Transfer learning approach to predict biopsy-confirmed malignancy of lung nodules from imaging data: a pilot study -- Convolutional Neural Network Based COPD and Emphysema Classifications Are Predictive of Lung Cancer Diagnosis -- Towards an automatic lung cancer screening system in low dose computed tomography -- Automatic classification of centrilobular emphysema on CT using deep learning: comparison with visual scoring -- On the Relevance of the Loss Function in the Agatston Score Regression from non-ECG Gated CT Scans -- Accurate Measurement of Airway Morphology on Chest CT images. |
Record Nr. | UNISA-996466186203316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Image Analysis for Moving Organ, Breast, and Thoracic Images : Third International Workshop, RAMBO 2018, Fourth International Workshop, BIA 2018, and First International Workshop, TIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16 and 20, 2018, Proceedings / / edited by Danail Stoyanov, Zeike Taylor, Bernhard Kainz, Gabriel Maicas, Reinhard R. Beichel, Anne Martel, Lena Maier-Hein, Kanwal Bhatia, Tom Vercauteren, Ozan Oktay, Gustavo Carneiro, Andrew P. Bradley, Jacinto Nascimento, Hang Min, Matthew S. Brown, Colin Jacobs, Bianca Lassen-Schmidt, Kensaku Mori, Jens Petersen, Raúl San José Estépar, Alexander Schmidt-Richberg, Catarina Veiga |
Edizione | [1st ed. 2018.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
Descrizione fisica | 1 online resource (xiv, 350 pages) : illustrations (chiefly color) |
Disciplina | 616.0754 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Artificial intelligence Health informatics Computers Image Processing and Computer Vision Artificial Intelligence Health Informatics Information Systems and Communication Service |
ISBN | 3-030-00946-7 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Resection-based Demons Regularization for Breast Tumor Bed Propagation -- Linear and Deformable Image Registration with 3D Convolutional Neural Networks -- Super Resolution of Cardiac Cine MRI Sequences Using Deep Learning -- Automated CNN-based Reconstruction of Short-Axis Cardiac MR Sequence From Real-Time Image Data -- An Unbiased Groupwise Registration Algorithm for Correcting Motion in Dynamic Contrast-Enhanced Magnetic Resonance Images -- Siamese Network for Dual-View Mammography Mass Matching -- Large-scale Mammography CAD with Deformable Conv-Nets -- Domain Adaptation for Deviating Acquisition Protocols in CNN-based Lesion Classification on Diffusion-Weighted MR Images -- Improved Breast Mass Segmentation in Mammograms with Conditional Residual U-net -- Improving Breast Cancer Detection using Symmetry Information -- Conditional Infilling GANs for Data Augmentation in Mammogram Classification -- A Unified Mammogram Analysis Method via Hybrid Deep Supervision -- Structure-aware Staging for Breast Cancer Metastases -- Reproducible evaluation of registration algorithms for movement correction in dynamic contrast enhancing magnetic resonance imaging for breast cancer diagnosis -- Robust Windowed Harmonic Phase Analysis with a Single Acquisition -- Lung Structures Enhancement in Chest Radiographs via CT based FCNN Training -- Improving the Segmentation of Anatomical Structures in Chest Radiographs using U-Net with an ImageNet Pre-trained Encoder -- Tuberculosis histopathology on x-ray CT -- A CT scan harmonization technique to detect Emphysema and Small Airway Diseases -- Transfer Learning for Segmentation of Injured Lungs using Coarse-to-Fine Convolutional Neural Networks -- High throughput lung and lobar segmentation by 2D and 3D CNN on chest CT with diffuse lung disease -- Multi-Structure Segmentation from Partially Labeled Datasets. Application to Body Composition Measurements on CT scans -- 3D Pulmonary Artery Segmentation from CTA Scans using Deep Learning with Realistic Data Augmentation -- Automatic Airway Segmentation in chest CT using Convolutional Neural Networks -- Detecting Out-of-phase Ventilation Using 4DCT to Improve Radiation Therapy for Lung Cancer -- XeMRI to CT Lung Image Registration Enhanced with Personalized 4DCT-derived Motion Model -- Rigid Lens – Locally Rigid Approximations of Deformable Registration for Change Assessment in Thorax-Abdomen CT Follow-Up Scan -- Diffeomorphic Lung Registration using Deep CNNs and Reinforced Learning -- Transfer learning approach to predict biopsy-confirmed malignancy of lung nodules from imaging data: a pilot study -- Convolutional Neural Network Based COPD and Emphysema Classifications Are Predictive of Lung Cancer Diagnosis -- Towards an automatic lung cancer screening system in low dose computed tomography -- Automatic classification of centrilobular emphysema on CT using deep learning: comparison with visual scoring -- On the Relevance of the Loss Function in the Agatston Score Regression from non-ECG Gated CT Scans -- Accurate Measurement of Airway Morphology on Chest CT images. |
Record Nr. | UNINA-9910349407203321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Machine Learning Meets Medical Imaging [[electronic resource] ] : First International Workshop, MLMMI 2015, Held in Conjunction with ICML 2015, Lille, France, July 11, 2015, Revised Selected Papers / / edited by Kanwal Bhatia, Herve Lombaert |
Edizione | [1st ed. 2015.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
Descrizione fisica | 1 online resource (X, 105 p. 31 illus. in color.) |
Disciplina | 006.31 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Artificial intelligence Bioinformatics Pattern recognition Algorithms Computers Image Processing and Computer Vision Artificial Intelligence Computational Biology/Bioinformatics Pattern Recognition Algorithm Analysis and Problem Complexity Computation by Abstract Devices |
ISBN | 3-319-27929-7 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Retrospective motion correction of magnitude-input MR images -- Automatic Brain Localization in Fetal MRI Using Superpixel Graphs -- Learning Deep Temporal Representations for fMRI Brain Decoding -- Modelling Non-Stationary and Non-Separable Spatio-Temporal Changes in Neurodegeneration via Gaussian Process Convolution -- Improving MRI brain image classification with anatomical regional kernels -- A Graph Based Classification Method for Multiple Sclerosis Clinical Form Using Support Vector Machine -- Classification of Alzheimer’s Disease using Discriminant Manifolds of Hippocampus Shapes -- Transfer Learning for Prostate Cancer Mapping Based on Multicentric MR imaging databases. |
Record Nr. | UNISA-996466073303316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Machine Learning Meets Medical Imaging : First International Workshop, MLMMI 2015, Held in Conjunction with ICML 2015, Lille, France, July 11, 2015, Revised Selected Papers / / edited by Kanwal Bhatia, Herve Lombaert |
Edizione | [1st ed. 2015.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
Descrizione fisica | 1 online resource (X, 105 p. 31 illus. in color.) |
Disciplina | 006.31 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Artificial intelligence Bioinformatics Pattern recognition Algorithms Computers Image Processing and Computer Vision Artificial Intelligence Computational Biology/Bioinformatics Pattern Recognition Algorithm Analysis and Problem Complexity Computation by Abstract Devices |
ISBN | 3-319-27929-7 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Retrospective motion correction of magnitude-input MR images -- Automatic Brain Localization in Fetal MRI Using Superpixel Graphs -- Learning Deep Temporal Representations for fMRI Brain Decoding -- Modelling Non-Stationary and Non-Separable Spatio-Temporal Changes in Neurodegeneration via Gaussian Process Convolution -- Improving MRI brain image classification with anatomical regional kernels -- A Graph Based Classification Method for Multiple Sclerosis Clinical Form Using Support Vector Machine -- Classification of Alzheimer’s Disease using Discriminant Manifolds of Hippocampus Shapes -- Transfer Learning for Prostate Cancer Mapping Based on Multicentric MR imaging databases. |
Record Nr. | UNINA-9910484961003321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Reconstruction, Segmentation, and Analysis of Medical Images [[electronic resource] ] : First International Workshops, RAMBO 2016 and HVSMR 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected Papers / / edited by Maria A. Zuluaga, Kanwal Bhatia, Bernhard Kainz, Mehdi H. Moghari, Danielle F. Pace |
Edizione | [1st ed. 2017.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
Descrizione fisica | 1 online resource (XI, 174 p. 67 illus.) |
Disciplina | 616.0754 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Image Processing and Computer Vision |
ISBN | 3-319-52280-9 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Registration -- Reconstruction -- Deep learning for heart segmentation -- Discrete optimization and probabilistic intensity modeling -- Atlas-based strategies -- Random forests. |
Record Nr. | UNISA-996465747503316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Reconstruction, Segmentation, and Analysis of Medical Images : First International Workshops, RAMBO 2016 and HVSMR 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected Papers / / edited by Maria A. Zuluaga, Kanwal Bhatia, Bernhard Kainz, Mehdi H. Moghari, Danielle F. Pace |
Edizione | [1st ed. 2017.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
Descrizione fisica | 1 online resource (XI, 174 p. 67 illus.) |
Disciplina | 616.0754 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Image Processing and Computer Vision |
ISBN | 3-319-52280-9 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Registration -- Reconstruction -- Deep learning for heart segmentation -- Discrete optimization and probabilistic intensity modeling -- Atlas-based strategies -- Random forests. |
Record Nr. | UNINA-9910483751603321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|