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 | ||
![]() | ||
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 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment [[electronic resource] ] : Fifth International Workshop, CMMI 2017, Second International Workshop, RAMBO 2017, and First International Workshop, SWITCH 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, 2017, Proceedings / / edited by M. Jorge Cardoso, Tal Arbel, Fei Gao, Bernhard Kainz, Theo van Walsum, Kuangyu Shi, Kanwal K. Bhatia, Roman Peter, Tom Vercauteren, Mauricio Reyes, Adrian Dalca, Roland Wiest, Wiro Niessen, Bart J. Emmer |
Edizione | [1st ed. 2017.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
Descrizione fisica | 1 online resource (XV, 186 p. 74 illus.) |
Disciplina | 616.07540285 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Health informatics Information storage and retrieval Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Health Informatics Information Storage and Retrieval |
ISBN | 3-319-67564-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Workshop Editors -- Preface CMMI 2017 -- Organization -- Preface RAMBO 2017 -- Organization -- Preface SWITCH 2017 -- Organization -- Contents -- Fifth International Workshop on Computational Methods for Molecular Imaging, CMMI 2017 -- 3D Lymphoma Segmentation in PET/CT Images Based on Fully Connected CRFs -- Abstract -- 1 Introduction -- 2 Method -- 2.1 The Fully Connected CRFs Model -- 2.2 Inference of CRFs Model -- 3 Evaluation and Results -- 3.1 Database -- 3.2 Evaluation Metrics -- 3.3 Estimation of the Parameters in CRF Model -- 3.4 Results -- 4 Conclusion and Perspectives -- References -- Individual Analysis of Molecular Brain Imaging Data Through Automatic Identification of Abnormality Patterns -- 1 Introduction -- 2 Methods -- 2.1 Data -- 2.2 Data Preprocessing -- 2.3 Subject-Specific Analysis of PET Data -- 2.4 Validation Scheme -- 3 Results -- 4 Discussion and Conclusion -- References -- W-Net for Whole-Body Bone Lesion Detection on 68Ga-Pentixafor PET/CT Imaging of Multiple Myeloma Patients -- 1 Introduction -- 2 Method and Experiment -- 2.1 Data Preparation and Preprocessing -- 2.2 W-Net Deep Learning Architecture -- 3 Results and Discussion -- 4 Conclusion -- References -- 3D Alpha Matting Based Co-segmentation of Tumors on PET-CT Images -- 1 Introduction -- 2 Methodology -- 2.1 Active Contour Based 3D Trimap Generation -- 2.2 3D Alpha Matting Based Tumor Object Probability Maps -- 2.3 Context-Aware Co-segmentation -- 3 Experiment -- 3.1 Datasets -- 3.2 Experiment Settings -- 3.3 Results and Analysis -- 4 Conclusion -- References -- Synthesis of Positron Emission Tomography (PET) Images via Multi-channel Generative Adversarial Networks (GANs) -- 1 Introduction -- 2 Methods -- 2.1 Multi-channel Generative Adversarial Networks (M-GANs) -- 2.2 Materials and Implementation Details -- 3 Evaluation.
3.1 Experimental Results for PET Image Synthesis -- 3.2 Using Synthetic PET Images for Training -- 4 Discussion -- 5 Conclusion -- References -- Second International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2017 -- Dynamic Respiratory Motion Estimation Using Patch-Based Kernel-PCA Priors for Lung Cancer Radiotherapy -- Abstract -- 1 Introduction -- 2 Method -- 2.1 Statistical Respiratory Motion Patterns -- 2.2 Patch-Based Linear and Nonlinear Motion Estimation -- 3 Results -- 4 Conclusion -- References -- Mass Transportation for Deformable Image Registration with Application to Lung CT -- 1 Introduction -- 2 Methods -- 3 Experiments and Results -- 4 Discussion and Conclusions -- References -- Motion-Robust Spatially Constrained Parameter Estimation in Renal Diffusion-Weighted MRI by 3D Motion Tracking and Correction of Sequential Slices -- 1 Introduction -- 2 Methods -- 2.1 Renal DW-MRI Acquisition -- 2.2 3D Motion Tracking and Correction of Sequentially Acquired Slices -- 2.3 Spatially Constrained IVIM Parameter Estimation -- 2.4 Weighted Least Squares Diffusion Tensor Model Estimation -- 3 Results -- 4 Conclusion -- References -- Semi-automatic Cardiac and Respiratory Gated MRI for Cardiac Assessment During Exercise -- 1 Introduction -- 2 Methods -- 2.1 Highly Accelerated Dynamic MRI -- 2.2 Cardiac Synchronization -- 2.3 Respiratory Gating -- 2.4 Cine Reconstruction -- 3 Experiments and Results -- 4 Discussion -- References -- CoronARe: A Coronary Artery Reconstruction Challenge -- 1 Introduction -- 2 Materials and Methods -- 2.1 Scope and Specific Goals -- 2.2 Data -- 2.3 Evaluation Protocol and Ranking -- 2.4 Ranking -- 2.5 Submission Guidelines and Formats -- 3 Discussion and Outlook -- References -- Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networks -- Abstract. 1 Introduction -- 2 Method -- 2.1 Spatially-Conditioned Generative Adversarial Learning -- 2.2 Network Architecture -- 2.3 Validation Experiment -- 3 Results -- 4 Conclusion and Discussion -- Acknowledgement -- References -- Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging -- 1 Introduction -- 2 Method -- 3 Experiments -- 4 Evaluation and Results -- 5 Discussion and Conclusion -- References -- Reconstruction of 3D Cardiac MR Images from 2D Slices Using Directional Total Variation -- 1 Introduction -- 2 Materials and Methods -- 2.1 Image Acquisition -- 2.2 Super-Resolution Algorithm -- 2.3 Validation -- 3 Results -- 4 Discussion and Conclusion -- References -- An Efficient Multi-resolution Reconstruction Scheme with Motion Compensation for 5D Free-Breathing Whole-Heart MRI -- 1 Introduction -- 2 Material and Methods -- 2.1 Compressed Sensing Reconstruction -- 2.2 Motion Compensated MRI Reconstruction -- 2.3 Extra-Dimensinal (XD) MRI Reconstruction -- 2.4 Multi-resolution Strategy for MC-XD MRI Reconstruction -- 2.5 Data and Experiments Description -- 3 Results and Discussion -- 4 Conclusion -- References -- First International Stroke Workshop on Imaging and Treatment Challenges, SWITCH 2017 -- Automated Ventricular System Segmentation in CT Images of Deformed Brains Due to Ischemic and Subara ... -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Patient Selection -- 2.2 Method Overview -- 2.3 Accuracy -- 3 Results -- 4 Discussion -- References -- Towards Automatic Collateral Circulation Score Evaluation in Ischemic Stroke Using Image Decompositi ... -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Subjects and Scanning Protocols -- 2.2 Collateral Circulation Scoring for Patients -- 2.3 Image Processing -- 2.4 Blood Vessel Extraction -- 2.5 Eigen Vessel Patterns and Score Assignment. 2.6 Training and Validation -- 3 Results -- 3.1 Low-Rank Image Decomposition -- 3.2 Eigen Vessel Patterns -- 3.3 Automatic Collateral Circulation Scoring Results -- 4 Discussion and Future Work -- 5 Conclusions -- References -- The Effect of Non-contrast CT Slice Thickness on Thrombus Density and Perviousness Assessment -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Patient Selection -- 2.2 Slice Reconstruction -- 2.3 Density and Perviousness Measurements -- 2.4 Statistical Analysis -- 3 Results -- 4 Discussion -- 5 Conclusion -- Acknowledgements -- References -- Quantitative Collateral Grading on CT Angiography in Patients with Acute Ischemic Stroke -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Patient Selection -- 2.2 Outcomes -- 2.3 Manual Collateral Score -- 2.4 Quantitative Collateral Score -- 2.5 Assessment of Tissue Outcome -- 2.6 Statistical Analysis -- 3 Results -- 4 Discussion -- Funding -- References -- Author Index. |
Record Nr. | UNISA-996466238603316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
![]() | ||
Lo trovi qui: Univ. di Salerno | ||
|
Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment : Fifth International Workshop, CMMI 2017, Second International Workshop, RAMBO 2017, and First International Workshop, SWITCH 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, 2017, Proceedings / / edited by M. Jorge Cardoso, Tal Arbel, Fei Gao, Bernhard Kainz, Theo van Walsum, Kuangyu Shi, Kanwal K. Bhatia, Roman Peter, Tom Vercauteren, Mauricio Reyes, Adrian Dalca, Roland Wiest, Wiro Niessen, Bart J. Emmer |
Edizione | [1st ed. 2017.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
Descrizione fisica | 1 online resource (XV, 186 p. 74 illus.) |
Disciplina | 616.07540285 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Health informatics Information storage and retrieval Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Health Informatics Information Storage and Retrieval |
ISBN | 3-319-67564-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Workshop Editors -- Preface CMMI 2017 -- Organization -- Preface RAMBO 2017 -- Organization -- Preface SWITCH 2017 -- Organization -- Contents -- Fifth International Workshop on Computational Methods for Molecular Imaging, CMMI 2017 -- 3D Lymphoma Segmentation in PET/CT Images Based on Fully Connected CRFs -- Abstract -- 1 Introduction -- 2 Method -- 2.1 The Fully Connected CRFs Model -- 2.2 Inference of CRFs Model -- 3 Evaluation and Results -- 3.1 Database -- 3.2 Evaluation Metrics -- 3.3 Estimation of the Parameters in CRF Model -- 3.4 Results -- 4 Conclusion and Perspectives -- References -- Individual Analysis of Molecular Brain Imaging Data Through Automatic Identification of Abnormality Patterns -- 1 Introduction -- 2 Methods -- 2.1 Data -- 2.2 Data Preprocessing -- 2.3 Subject-Specific Analysis of PET Data -- 2.4 Validation Scheme -- 3 Results -- 4 Discussion and Conclusion -- References -- W-Net for Whole-Body Bone Lesion Detection on 68Ga-Pentixafor PET/CT Imaging of Multiple Myeloma Patients -- 1 Introduction -- 2 Method and Experiment -- 2.1 Data Preparation and Preprocessing -- 2.2 W-Net Deep Learning Architecture -- 3 Results and Discussion -- 4 Conclusion -- References -- 3D Alpha Matting Based Co-segmentation of Tumors on PET-CT Images -- 1 Introduction -- 2 Methodology -- 2.1 Active Contour Based 3D Trimap Generation -- 2.2 3D Alpha Matting Based Tumor Object Probability Maps -- 2.3 Context-Aware Co-segmentation -- 3 Experiment -- 3.1 Datasets -- 3.2 Experiment Settings -- 3.3 Results and Analysis -- 4 Conclusion -- References -- Synthesis of Positron Emission Tomography (PET) Images via Multi-channel Generative Adversarial Networks (GANs) -- 1 Introduction -- 2 Methods -- 2.1 Multi-channel Generative Adversarial Networks (M-GANs) -- 2.2 Materials and Implementation Details -- 3 Evaluation.
3.1 Experimental Results for PET Image Synthesis -- 3.2 Using Synthetic PET Images for Training -- 4 Discussion -- 5 Conclusion -- References -- Second International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2017 -- Dynamic Respiratory Motion Estimation Using Patch-Based Kernel-PCA Priors for Lung Cancer Radiotherapy -- Abstract -- 1 Introduction -- 2 Method -- 2.1 Statistical Respiratory Motion Patterns -- 2.2 Patch-Based Linear and Nonlinear Motion Estimation -- 3 Results -- 4 Conclusion -- References -- Mass Transportation for Deformable Image Registration with Application to Lung CT -- 1 Introduction -- 2 Methods -- 3 Experiments and Results -- 4 Discussion and Conclusions -- References -- Motion-Robust Spatially Constrained Parameter Estimation in Renal Diffusion-Weighted MRI by 3D Motion Tracking and Correction of Sequential Slices -- 1 Introduction -- 2 Methods -- 2.1 Renal DW-MRI Acquisition -- 2.2 3D Motion Tracking and Correction of Sequentially Acquired Slices -- 2.3 Spatially Constrained IVIM Parameter Estimation -- 2.4 Weighted Least Squares Diffusion Tensor Model Estimation -- 3 Results -- 4 Conclusion -- References -- Semi-automatic Cardiac and Respiratory Gated MRI for Cardiac Assessment During Exercise -- 1 Introduction -- 2 Methods -- 2.1 Highly Accelerated Dynamic MRI -- 2.2 Cardiac Synchronization -- 2.3 Respiratory Gating -- 2.4 Cine Reconstruction -- 3 Experiments and Results -- 4 Discussion -- References -- CoronARe: A Coronary Artery Reconstruction Challenge -- 1 Introduction -- 2 Materials and Methods -- 2.1 Scope and Specific Goals -- 2.2 Data -- 2.3 Evaluation Protocol and Ranking -- 2.4 Ranking -- 2.5 Submission Guidelines and Formats -- 3 Discussion and Outlook -- References -- Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networks -- Abstract. 1 Introduction -- 2 Method -- 2.1 Spatially-Conditioned Generative Adversarial Learning -- 2.2 Network Architecture -- 2.3 Validation Experiment -- 3 Results -- 4 Conclusion and Discussion -- Acknowledgement -- References -- Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging -- 1 Introduction -- 2 Method -- 3 Experiments -- 4 Evaluation and Results -- 5 Discussion and Conclusion -- References -- Reconstruction of 3D Cardiac MR Images from 2D Slices Using Directional Total Variation -- 1 Introduction -- 2 Materials and Methods -- 2.1 Image Acquisition -- 2.2 Super-Resolution Algorithm -- 2.3 Validation -- 3 Results -- 4 Discussion and Conclusion -- References -- An Efficient Multi-resolution Reconstruction Scheme with Motion Compensation for 5D Free-Breathing Whole-Heart MRI -- 1 Introduction -- 2 Material and Methods -- 2.1 Compressed Sensing Reconstruction -- 2.2 Motion Compensated MRI Reconstruction -- 2.3 Extra-Dimensinal (XD) MRI Reconstruction -- 2.4 Multi-resolution Strategy for MC-XD MRI Reconstruction -- 2.5 Data and Experiments Description -- 3 Results and Discussion -- 4 Conclusion -- References -- First International Stroke Workshop on Imaging and Treatment Challenges, SWITCH 2017 -- Automated Ventricular System Segmentation in CT Images of Deformed Brains Due to Ischemic and Subara ... -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Patient Selection -- 2.2 Method Overview -- 2.3 Accuracy -- 3 Results -- 4 Discussion -- References -- Towards Automatic Collateral Circulation Score Evaluation in Ischemic Stroke Using Image Decompositi ... -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Subjects and Scanning Protocols -- 2.2 Collateral Circulation Scoring for Patients -- 2.3 Image Processing -- 2.4 Blood Vessel Extraction -- 2.5 Eigen Vessel Patterns and Score Assignment. 2.6 Training and Validation -- 3 Results -- 3.1 Low-Rank Image Decomposition -- 3.2 Eigen Vessel Patterns -- 3.3 Automatic Collateral Circulation Scoring Results -- 4 Discussion and Future Work -- 5 Conclusions -- References -- The Effect of Non-contrast CT Slice Thickness on Thrombus Density and Perviousness Assessment -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Patient Selection -- 2.2 Slice Reconstruction -- 2.3 Density and Perviousness Measurements -- 2.4 Statistical Analysis -- 3 Results -- 4 Discussion -- 5 Conclusion -- Acknowledgements -- References -- Quantitative Collateral Grading on CT Angiography in Patients with Acute Ischemic Stroke -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Patient Selection -- 2.2 Outcomes -- 2.3 Manual Collateral Score -- 2.4 Quantitative Collateral Score -- 2.5 Assessment of Tissue Outcome -- 2.6 Statistical Analysis -- 3 Results -- 4 Discussion -- Funding -- References -- Author Index. |
Record Nr. | UNINA-9910484560903321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
![]() | ||
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 | ||
![]() | ||
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 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|