Graph Learning in Medical Imaging [[electronic resource] ] : First International Workshop, GLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings / / edited by Daoqiang Zhang, Luping Zhou, Biao Jie, Mingxia Liu |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (IX, 182 p. 87 illus., 68 illus. in color.) |
Disciplina | 006.3 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Artificial intelligence
Optical data processing Pattern recognition Application software Artificial Intelligence Image Processing and Computer Vision Pattern Recognition Computer Appl. in Social and Behavioral Sciences |
ISBN | 3-030-35817-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Graph Hyperalignment for Multi-Subject fMRI Functional Alignment -- Interactive 3D Segmentation Editing and Refinement via Gated Graph Neural Networks -- Adaptive Thresholding of Functional Connectivity Networks for fMRI-based Brain Disease Analysis -- Graph-kernel-based Multi-task Structured Feature Selection on Multi-level Functional Connectivity Networks for Brain Disease Classification -- Linking convolutional neural networks with graph convolutional networks: application in pulmonary artery-vein separation -- Comparative Analysis of Magnetic Resonance Fingerprinting Dictionaries via Dimensionality Reduction -- Learning Deformable Point Set Registration with Regularized Dynamic Graph CNNs for Large Lung Motion in COPD Patients -- Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography -- Triplet Graph Convolutional Network forMulti-scale Analysis of Functional Connectivityusing Functional MRI -- Multi-Scale Graph Convolutional Network for Mild Cognitive Impairment Detection -- DeepBundle: Fiber Bundle Parcellation With Graph CNNs -- Identification of Functional Connectivity Features in Depression Subtypes Using a Data-Driven Approach -- Movie-watching fMRI Reveals Inter-subject Synchrony Alteration in Functional Brain Activity in ADHD -- Weakly- and Semi- Supervised Graph CNN for identifying Basal Cell Carcinoma on Pathological images -- Geometric Brain Surface Network For Brain Cortical Parcellation -- Automatic Detection of Craniomaxillofacial Anatomical Landmarks on CBCT Images using 3D Mask R-CNN -- Discriminative-Region-Aware Residual Network for Adolescent Brain Structure and Cognitive Development Analysis -- Graph Modeling for Identifying Breast Tumor Located in Dense Background of a Mammogram -- OCD Diagnosis via Smoothing Sparse Network and Stacked Sparse Auto-Encoder Learning -- A Longitudinal MRI Study of Amygdala and Hippocampal Subfields for Infants with Risk of Autism -- CNS: CycleGAN-assisted Neonatal Segmentation Model for Cross-Datasets. |
Record Nr. | UNINA-9910357848303321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
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Lo trovi qui: Univ. Federico II | ||
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Graph Learning in Medical Imaging [[electronic resource] ] : First International Workshop, GLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings / / edited by Daoqiang Zhang, Luping Zhou, Biao Jie, Mingxia Liu |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (IX, 182 p. 87 illus., 68 illus. in color.) |
Disciplina | 006.3 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Artificial intelligence
Optical data processing Pattern recognition Application software Artificial Intelligence Image Processing and Computer Vision Pattern Recognition Computer Appl. in Social and Behavioral Sciences |
ISBN | 3-030-35817-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Graph Hyperalignment for Multi-Subject fMRI Functional Alignment -- Interactive 3D Segmentation Editing and Refinement via Gated Graph Neural Networks -- Adaptive Thresholding of Functional Connectivity Networks for fMRI-based Brain Disease Analysis -- Graph-kernel-based Multi-task Structured Feature Selection on Multi-level Functional Connectivity Networks for Brain Disease Classification -- Linking convolutional neural networks with graph convolutional networks: application in pulmonary artery-vein separation -- Comparative Analysis of Magnetic Resonance Fingerprinting Dictionaries via Dimensionality Reduction -- Learning Deformable Point Set Registration with Regularized Dynamic Graph CNNs for Large Lung Motion in COPD Patients -- Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography -- Triplet Graph Convolutional Network forMulti-scale Analysis of Functional Connectivityusing Functional MRI -- Multi-Scale Graph Convolutional Network for Mild Cognitive Impairment Detection -- DeepBundle: Fiber Bundle Parcellation With Graph CNNs -- Identification of Functional Connectivity Features in Depression Subtypes Using a Data-Driven Approach -- Movie-watching fMRI Reveals Inter-subject Synchrony Alteration in Functional Brain Activity in ADHD -- Weakly- and Semi- Supervised Graph CNN for identifying Basal Cell Carcinoma on Pathological images -- Geometric Brain Surface Network For Brain Cortical Parcellation -- Automatic Detection of Craniomaxillofacial Anatomical Landmarks on CBCT Images using 3D Mask R-CNN -- Discriminative-Region-Aware Residual Network for Adolescent Brain Structure and Cognitive Development Analysis -- Graph Modeling for Identifying Breast Tumor Located in Dense Background of a Mammogram -- OCD Diagnosis via Smoothing Sparse Network and Stacked Sparse Auto-Encoder Learning -- A Longitudinal MRI Study of Amygdala and Hippocampal Subfields for Infants with Risk of Autism -- CNS: CycleGAN-assisted Neonatal Segmentation Model for Cross-Datasets. |
Record Nr. | UNISA-996466431003316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
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Lo trovi qui: Univ. di Salerno | ||
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Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention [[electronic resource] ] : International Workshops, LABELS 2019, HAL-MICCAI 2019, and CuRIOUS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings / / edited by Luping Zhou, Nicholas Heller, Yiyu Shi, Yiming Xiao, Raphael Sznitman, Veronika Cheplygina, Diana Mateus, Emanuele Trucco, X. Sharon Hu, Danny Chen, Matthieu Chabanas, Hassan Rivaz, Ingerid Reinertsen |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (XX, 154 p. 62 illus., 48 illus. in color.) |
Disciplina |
006.6
006.37 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Artificial intelligence Health informatics Image Processing and Computer Vision Artificial Intelligence Health Informatics |
ISBN | 3-030-33642-5 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | 4th International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis (LABELS 2019) -- Comparison of active learning strategies applied to lung nodule segmentation in CT scans -- Robust Registration of Statistical Shape Models for Unsupervised Pathology Annotation -- XiangyaDerm: A Clinical Image Dataset of Asian Race for Skin Disease Aided Diagnosis -- Data Augmentation based on Substituting Regional MRI Volume Scores -- Weakly supervised segmentation from extreme points -- Exploring the Relationship between Segmentation Uncertainty, Segmentation Performance and Inter-observer Variability with Probabilistic Networks -- DeepIGeoS-V2: Deep Interactive Segmentation of Multiple Organs from Head and Neck Images with Lightweight CNNs -- The Role of Publicly Available Data in MICCAI Papers from 2014 to 2018 -- First International Workshop on Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention (HAL-MICCAI 2019) -- Hardware Acceleration of Persistent Homology Computation -- Deep Compressed Pneumonia Detection for Low-Power Embedded Devices -- D3MC: A Reinforcement Learning based Data-driven Dyna Model Compression -- An Analytical Method of Automatic Alignment for Electron Tomography -- Fixed-Point U-Net Quantization for Medical Image Segmentation -- Second International Workshop on Correction of Brainshift with Intra-Operative Ultrasound (CuRIOUS 2019) -- Registration of ultrasound volumes based on Euclidean distance transform -- Landmark-based evaluation of a block-matching registration framework on the RESECT pre- and intra-operative brain image data set -- Comparing deep learning strategies and attention mechanisms of discrete registration for multimodal image-guided interventions. |
Record Nr. | UNINA-9910357847003321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
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Lo trovi qui: Univ. Federico II | ||
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Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention [[electronic resource] ] : International Workshops, LABELS 2019, HAL-MICCAI 2019, and CuRIOUS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings / / edited by Luping Zhou, Nicholas Heller, Yiyu Shi, Yiming Xiao, Raphael Sznitman, Veronika Cheplygina, Diana Mateus, Emanuele Trucco, X. Sharon Hu, Danny Chen, Matthieu Chabanas, Hassan Rivaz, Ingerid Reinertsen |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (XX, 154 p. 62 illus., 48 illus. in color.) |
Disciplina |
006.6
006.37 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Artificial intelligence Health informatics Image Processing and Computer Vision Artificial Intelligence Health Informatics |
ISBN | 3-030-33642-5 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | 4th International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis (LABELS 2019) -- Comparison of active learning strategies applied to lung nodule segmentation in CT scans -- Robust Registration of Statistical Shape Models for Unsupervised Pathology Annotation -- XiangyaDerm: A Clinical Image Dataset of Asian Race for Skin Disease Aided Diagnosis -- Data Augmentation based on Substituting Regional MRI Volume Scores -- Weakly supervised segmentation from extreme points -- Exploring the Relationship between Segmentation Uncertainty, Segmentation Performance and Inter-observer Variability with Probabilistic Networks -- DeepIGeoS-V2: Deep Interactive Segmentation of Multiple Organs from Head and Neck Images with Lightweight CNNs -- The Role of Publicly Available Data in MICCAI Papers from 2014 to 2018 -- First International Workshop on Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention (HAL-MICCAI 2019) -- Hardware Acceleration of Persistent Homology Computation -- Deep Compressed Pneumonia Detection for Low-Power Embedded Devices -- D3MC: A Reinforcement Learning based Data-driven Dyna Model Compression -- An Analytical Method of Automatic Alignment for Electron Tomography -- Fixed-Point U-Net Quantization for Medical Image Segmentation -- Second International Workshop on Correction of Brainshift with Intra-Operative Ultrasound (CuRIOUS 2019) -- Registration of ultrasound volumes based on Euclidean distance transform -- Landmark-based evaluation of a block-matching registration framework on the RESECT pre- and intra-operative brain image data set -- Comparing deep learning strategies and attention mechanisms of discrete registration for multimodal image-guided interventions. |
Record Nr. | UNISA-996466295103316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
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Lo trovi qui: Univ. di Salerno | ||
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Machine Learning in Medical Imaging [[electronic resource] ] : 6th International Workshop, MLMI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings / / edited by Luping Zhou, Li Wang, Qian Wang, Yinghuan Shi |
Edizione | [1st ed. 2015.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
Descrizione fisica | 1 online resource (XII, 341 p. 128 illus.) |
Disciplina | 616.07540285 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Pattern recognition Health informatics Data mining Artificial intelligence Image Processing and Computer Vision Pattern Recognition Health Informatics Data Mining and Knowledge Discovery Artificial Intelligence |
ISBN | 3-319-24888-X |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910483714403321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
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Lo trovi qui: Univ. Federico II | ||
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Machine Learning in Medical Imaging [[electronic resource] ] : 6th International Workshop, MLMI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings / / edited by Luping Zhou, Li Wang, Qian Wang, Yinghuan Shi |
Edizione | [1st ed. 2015.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
Descrizione fisica | 1 online resource (XII, 341 p. 128 illus.) |
Disciplina | 616.07540285 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Pattern recognition Health informatics Data mining Artificial intelligence Image Processing and Computer Vision Pattern Recognition Health Informatics Data Mining and Knowledge Discovery Artificial Intelligence |
ISBN | 3-319-24888-X |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISA-996466302803316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
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Lo trovi qui: Univ. di Salerno | ||
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Machine Learning in Medical Imaging [[electronic resource] ] : 5th International Workshop, MLMI 2014, Held in Conjunction with MICCAI 2014, Boston, MA, USA, September 14, 2014, Proceedings / / edited by Guorong Wu, Daoqiang Zhang, Luping Zhou |
Edizione | [1st ed. 2014.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 |
Descrizione fisica | 1 online resource (XII, 332 p. 136 illus.) |
Disciplina | 610.285 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Pattern recognition Health informatics Data mining Artificial intelligence Computer graphics Image Processing and Computer Vision Pattern Recognition Health Informatics Data Mining and Knowledge Discovery Artificial Intelligence Computer Graphics |
ISBN | 3-319-10581-7 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Sparsity-Learning-Based Longitudinal MR Image Registration for Early Brain Development -- Graph-Based Label Propagation in Fetal brain MR Images -- Deep Learning Based Automatic immune Cell Detection for Immunohistochemistry Images -- Stacked Multiscale Feature learning for Domain Independent Medical Image Segmentation -- Detection of Mammographic Masses by Content-Based Image Retrieval -- Inferring Sources of Dementia Progression with Network Diffusion Model -- 3D Intervertebral Disc Localization through Representation Learning with Knowledge Transfer -- Exploring Compact Representation of SICE Matrices for Functional Brain Network Classification -- Deep Learning for Cerebellar Ataxia Classification and Functional Score Regression -- Manifold Alignment and Transfer Learning for Classification of Alzheimer’s Disease -- Gleason Grading of Prostate Tumors with Max-Margin Conditional Random Fields -- Learning Distance Transform for Boundary Detection and Deformable Segmentation in CT Prostate Images -- Geodesic Geometric mean of Regional Covariance Descriptors as an Image-Level Descriptor for nuclear Atypia Grading in Breast Images -- A constrained Regression Forests Solution to 3D Fetal Ultrasound Plane Localization for Longitudinal Analysis of Brain Growth and Maturation -- Deep Learning of Image Features from Unlabeled Data for Multiple Sclerosis Lesion Segmentation -- Fetal Abdominal Standard Plane Localization through Representation Learning with Knowledge Transfer -- Searching for Structures of Interest in an Ultrasound Video Sequence -- Anatomically Constrained Weak Classifier Fusion for Early Detection of Alzheimer’s Disease -- Automatic Bone and Marrow Extraction from Dual Energy CT through SVM Margin-Based Multi-Material Decomposition Model Selection -- Sparse Discriminative Feature Selection for Multi-Class Alzheimer’s Disease Classification -- Context-aware Anatomical Landmark Detection: Application to Deformable Model Initialization in Prostate CT Images -- Optimal MAP Parameters Estimation in STAPLE-Learning from Performance Parameters versus Image Similarity Information -- Colon Biopsy Classification Using Crypt Architecture -- Network Guided Group Feature Selection for Classification of Autism Spectrum Disorder -- Deformation Field Correction for Spatial Normalization of PET Images Using a Population-derived Partial Least Squares Model -- Novel Multi-Atlas Segmentation by Matrix Completion -- Structured Random Forest for Myocardium Delineation in 3D Echocardiography -- Improved Reproducibility of Neuroanatomical Definition through Diffeomorphometry and Complexity Reduction -- Topological Descriptors of Histology Images -- Robust Deep Learning for Improved Classification of AD/MCI Patients -- Subject Specific Sparse Dictionary Learning for Atlas Based Brain MRI Segmentation -- Online Discriminative Multi-Atlas Learning with Application to Isointense Infant Brain Segmentation. . |
Record Nr. | UNISA-996215312403316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 | ||
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Lo trovi qui: Univ. di Salerno | ||
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Machine Learning in Medical Imaging [[electronic resource] ] : 5th International Workshop, MLMI 2014, Held in Conjunction with MICCAI 2014, Boston, MA, USA, September 14, 2014, Proceedings / / edited by Guorong Wu, Daoqiang Zhang, Luping Zhou |
Edizione | [1st ed. 2014.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 |
Descrizione fisica | 1 online resource (XII, 332 p. 136 illus.) |
Disciplina | 610.285 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Pattern recognition Health informatics Data mining Artificial intelligence Computer graphics Image Processing and Computer Vision Pattern Recognition Health Informatics Data Mining and Knowledge Discovery Artificial Intelligence Computer Graphics |
ISBN | 3-319-10581-7 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Sparsity-Learning-Based Longitudinal MR Image Registration for Early Brain Development -- Graph-Based Label Propagation in Fetal brain MR Images -- Deep Learning Based Automatic immune Cell Detection for Immunohistochemistry Images -- Stacked Multiscale Feature learning for Domain Independent Medical Image Segmentation -- Detection of Mammographic Masses by Content-Based Image Retrieval -- Inferring Sources of Dementia Progression with Network Diffusion Model -- 3D Intervertebral Disc Localization through Representation Learning with Knowledge Transfer -- Exploring Compact Representation of SICE Matrices for Functional Brain Network Classification -- Deep Learning for Cerebellar Ataxia Classification and Functional Score Regression -- Manifold Alignment and Transfer Learning for Classification of Alzheimer’s Disease -- Gleason Grading of Prostate Tumors with Max-Margin Conditional Random Fields -- Learning Distance Transform for Boundary Detection and Deformable Segmentation in CT Prostate Images -- Geodesic Geometric mean of Regional Covariance Descriptors as an Image-Level Descriptor for nuclear Atypia Grading in Breast Images -- A constrained Regression Forests Solution to 3D Fetal Ultrasound Plane Localization for Longitudinal Analysis of Brain Growth and Maturation -- Deep Learning of Image Features from Unlabeled Data for Multiple Sclerosis Lesion Segmentation -- Fetal Abdominal Standard Plane Localization through Representation Learning with Knowledge Transfer -- Searching for Structures of Interest in an Ultrasound Video Sequence -- Anatomically Constrained Weak Classifier Fusion for Early Detection of Alzheimer’s Disease -- Automatic Bone and Marrow Extraction from Dual Energy CT through SVM Margin-Based Multi-Material Decomposition Model Selection -- Sparse Discriminative Feature Selection for Multi-Class Alzheimer’s Disease Classification -- Context-aware Anatomical Landmark Detection: Application to Deformable Model Initialization in Prostate CT Images -- Optimal MAP Parameters Estimation in STAPLE-Learning from Performance Parameters versus Image Similarity Information -- Colon Biopsy Classification Using Crypt Architecture -- Network Guided Group Feature Selection for Classification of Autism Spectrum Disorder -- Deformation Field Correction for Spatial Normalization of PET Images Using a Population-derived Partial Least Squares Model -- Novel Multi-Atlas Segmentation by Matrix Completion -- Structured Random Forest for Myocardium Delineation in 3D Echocardiography -- Improved Reproducibility of Neuroanatomical Definition through Diffeomorphometry and Complexity Reduction -- Topological Descriptors of Histology Images -- Robust Deep Learning for Improved Classification of AD/MCI Patients -- Subject Specific Sparse Dictionary Learning for Atlas Based Brain MRI Segmentation -- Online Discriminative Multi-Atlas Learning with Application to Isointense Infant Brain Segmentation. . |
Record Nr. | UNINA-9910481958303321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 | ||
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Lo trovi qui: Univ. Federico II | ||
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OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging [[electronic resource] ] : Second International Workshop, OR 2.0 2019, and Second International Workshop, MLCN 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings / / edited by Luping Zhou, Duygu Sarikaya, Seyed Mostafa Kia, Stefanie Speidel, Anand Malpani, Daniel Hashimoto, Mohamad Habes, Tommy Löfstedt, Kerstin Ritter, Hongzhi Wang |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (XVI, 114 p. 35 illus., 33 illus. in color.) |
Disciplina | 617.00785 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Artificial intelligence Image Processing and Computer Vision Artificial Intelligence |
ISBN | 3-030-32695-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Proceedings of the Second International Workshop on OR 2.0 Context-Aware Operating Theaters (OR 2.0 2019) -- Feature Aggregation Decoder for Segmenting Laparoscopic Scenes -- Preoperative Planning for Guidewires employing Shape-Regularized Segmentation and Optimized Trajectories -- Guided unsupervised desmoking of laparoscopic images using Cycle-Desmoke -- Unsupervised Temporal Video Segmentation as an Auxiliary Task for Predicting the Remaining Surgery Duration -- Live monitoring of hemodynamic changes with multispectral image analysis -- Towards a Cyber-Physical Systems Based Operating Room of the Future -- Proceedings of the Second International Workshop on Machine Learning in Clinical Neuroimaging: Entering the era of big data via transfer learning and data harmonization (MLCN 2019) -- Deep Transfer Learning For Whole-Brain FMRI Analyses -- Knowledge distillation for semi-supervised domain adaptation -- Relevance Vector Machines for harmonization of MRI brain volumes using image descriptors -- Data Pooling and Sampling of Heterogeneous Image Data for White Matter Hyperintensity Segmentation -- A Hybrid 3DCNN and 3DC-LSTM based model for 4D Spatio-temporal fMRI data: An ABIDE Autism Classification study -- Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI across Sites. |
Record Nr. | UNISA-996466179903316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
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Lo trovi qui: Univ. di Salerno | ||
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OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging [[electronic resource] ] : Second International Workshop, OR 2.0 2019, and Second International Workshop, MLCN 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings / / edited by Luping Zhou, Duygu Sarikaya, Seyed Mostafa Kia, Stefanie Speidel, Anand Malpani, Daniel Hashimoto, Mohamad Habes, Tommy Löfstedt, Kerstin Ritter, Hongzhi Wang |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (XVI, 114 p. 35 illus., 33 illus. in color.) |
Disciplina | 617.00785 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Artificial intelligence Image Processing and Computer Vision Artificial Intelligence |
ISBN | 3-030-32695-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Proceedings of the Second International Workshop on OR 2.0 Context-Aware Operating Theaters (OR 2.0 2019) -- Feature Aggregation Decoder for Segmenting Laparoscopic Scenes -- Preoperative Planning for Guidewires employing Shape-Regularized Segmentation and Optimized Trajectories -- Guided unsupervised desmoking of laparoscopic images using Cycle-Desmoke -- Unsupervised Temporal Video Segmentation as an Auxiliary Task for Predicting the Remaining Surgery Duration -- Live monitoring of hemodynamic changes with multispectral image analysis -- Towards a Cyber-Physical Systems Based Operating Room of the Future -- Proceedings of the Second International Workshop on Machine Learning in Clinical Neuroimaging: Entering the era of big data via transfer learning and data harmonization (MLCN 2019) -- Deep Transfer Learning For Whole-Brain FMRI Analyses -- Knowledge distillation for semi-supervised domain adaptation -- Relevance Vector Machines for harmonization of MRI brain volumes using image descriptors -- Data Pooling and Sampling of Heterogeneous Image Data for White Matter Hyperintensity Segmentation -- A Hybrid 3DCNN and 3DC-LSTM based model for 4D Spatio-temporal fMRI data: An ABIDE Autism Classification study -- Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI across Sites. |
Record Nr. | UNINA-9910349273203321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
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Lo trovi qui: Univ. Federico II | ||
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