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