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Deep Learning and Data Labeling for Medical Applications [[electronic resource] ] : First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings / / edited by Gustavo Carneiro, Diana Mateus, Loïc Peter, Andrew Bradley, João Manuel R. S. Tavares, Vasileios Belagiannis, João Paulo Papa, Jacinto C. Nascimento, Marco Loog, Zhi Lu, Jaime S. Cardoso, Julien Cornebise
Deep Learning and Data Labeling for Medical Applications [[electronic resource] ] : First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings / / edited by Gustavo Carneiro, Diana Mateus, Loïc Peter, Andrew Bradley, João Manuel R. S. Tavares, Vasileios Belagiannis, João Paulo Papa, Jacinto C. Nascimento, Marco Loog, Zhi Lu, Jaime S. Cardoso, Julien Cornebise
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XIII, 280 p. 115 illus.)
Disciplina 610.285
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Artificial intelligence
Computer graphics
Health informatics
Image Processing and Computer Vision
Pattern Recognition
Artificial Intelligence
Computer Graphics
Health Informatics
ISBN 3-319-46976-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Active learning -- Semi-supervised learning -- Reinforcement learning -- Domain adaptation and transfer learning -- Crowd-sourcing annotations and fusion of labels from different sources -- Data augmentation -- Modelling of label uncertainty -- Visualization and human-computer interaction -- Image description -- Medical imaging-based diagnosis -- Medical signal-based diagnosis -- Medical image reconstruction and model selection using deep learning techniques -- Meta-heuristic techniques for fine-tuning -- Parameter in deep learning-based architectures -- Applications based on deep learning techniques.
Record Nr. UNISA-996465402503316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. di Salerno
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Deep Learning and Data Labeling for Medical Applications : First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings / / edited by Gustavo Carneiro, Diana Mateus, Loïc Peter, Andrew Bradley, João Manuel R. S. Tavares, Vasileios Belagiannis, João Paulo Papa, Jacinto C. Nascimento, Marco Loog, Zhi Lu, Jaime S. Cardoso, Julien Cornebise
Deep Learning and Data Labeling for Medical Applications : First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings / / edited by Gustavo Carneiro, Diana Mateus, Loïc Peter, Andrew Bradley, João Manuel R. S. Tavares, Vasileios Belagiannis, João Paulo Papa, Jacinto C. Nascimento, Marco Loog, Zhi Lu, Jaime S. Cardoso, Julien Cornebise
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XIII, 280 p. 115 illus.)
Disciplina 610.285
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Artificial intelligence
Computer graphics
Health informatics
Image Processing and Computer Vision
Pattern Recognition
Artificial Intelligence
Computer Graphics
Health Informatics
ISBN 3-319-46976-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Active learning -- Semi-supervised learning -- Reinforcement learning -- Domain adaptation and transfer learning -- Crowd-sourcing annotations and fusion of labels from different sources -- Data augmentation -- Modelling of label uncertainty -- Visualization and human-computer interaction -- Image description -- Medical imaging-based diagnosis -- Medical signal-based diagnosis -- Medical image reconstruction and model selection using deep learning techniques -- Meta-heuristic techniques for fine-tuning -- Parameter in deep learning-based architectures -- Applications based on deep learning techniques.
Record Nr. UNINA-9910483811703321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support [[electronic resource] ] : Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, Proceedings / / edited by M. Jorge Cardoso, Tal Arbel, Gustavo Carneiro, Tanveer Syeda-Mahmood, João Manuel R.S. Tavares, Mehdi Moradi, Andrew Bradley, Hayit Greenspan, João Paulo Papa, Anant Madabhushi, Jacinto C. Nascimento, Jaime S. Cardoso, Vasileios Belagiannis, Zhi Lu
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support [[electronic resource] ] : Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, Proceedings / / edited by M. Jorge Cardoso, Tal Arbel, Gustavo Carneiro, Tanveer Syeda-Mahmood, João Manuel R.S. Tavares, Mehdi Moradi, Andrew Bradley, Hayit Greenspan, João Paulo Papa, Anant Madabhushi, Jacinto C. Nascimento, Jaime S. Cardoso, Vasileios Belagiannis, Zhi Lu
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XIX, 385 p. 169 illus.)
Disciplina 006.42
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Artificial intelligence
Health informatics
Bioinformatics
Logic design
Image Processing and Computer Vision
Artificial Intelligence
Health Informatics
Computational Biology/Bioinformatics
Logic Design
ISBN 3-319-67558-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Workshop Editors -- Preface DLMIA 2017 -- Organization -- Preface ML-CDS 2017 -- Organization -- Contents -- Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017 -- Simultaneous Multiple Surface Segmentation Using Deep Learning -- 1 Introduction -- 2 Method -- 3 Experiments -- 4 Results -- 5 Discussion and Conclusion -- References -- A Deep Residual Inception Network for HEp-2 Cell Classification -- Abstract -- 1 Introduction -- 2 Deep Residual Inception -- 2.1 Network Architecture -- 2.2 DRI Module -- 2.3 Network Training -- 3 Results -- 3.1 Dataset -- 3.2 Data Augmentation -- 3.3 Performance Analysis -- 3.4 Comparisons -- 4 Conclusion -- References -- Joint Segmentation of Multiple Thoracic Organs in CT Images with Two Collaborative Deep Architectures -- 1 Introduction -- 2 Method -- 2.1 SharpMask Feature Fusion Architecture and CRF Refinement -- 2.2 Learning Anatomical Constraints -- 3 Experiments -- 3.1 Dataset and Pre-processing -- 3.2 Training -- 3.3 Results -- 4 Conclusions -- References -- Accelerated Magnetic Resonance Imaging by Adversarial Neural Network -- 1 Introduction -- 2 Method -- 2.1 K-space -- 2.2 Objective -- 2.3 Network Architecture -- 3 Experimental Results -- 4 Conclusions -- References -- Left Atrium Segmentation in CT Volumes with Fully Convolutional Networks -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Preprocessing -- 3.2 Fully Convolutional Network -- 3.3 Shape Constraints -- 4 Experiments -- 5 Conclusion -- References -- 3D Randomized Connection Network with Graph-Based Inference -- 1 Introduction -- 2 Methodology -- 2.1 Convolutional LSTM and 3D Convolution -- 2.2 Randomized Connection Network -- 2.3 Graph-Based Inference -- 3 Experiment -- 4 Conclusion -- References -- Adversarial Training and Dilated Convolutions for Brain MRI Segmentation -- 1 Introduction.
2 Materials and Methods -- 2.1 Data -- 2.2 Network Architecture -- 2.3 Adversarial Training -- 3 Experiments and Results -- 3.1 Experiments -- 3.2 Evaluation -- 4 Discussion and Conclusions -- References -- CNNs Enable Accurate and Fast Segmentation of Drusen in Optical Coherence Tomography -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Data Preparation -- 3.2 Network Architecture and Training -- 3.3 Three Approaches to Drusen Segmentation -- 4 Experiments and Results -- 4.1 Cross-Validation Setup -- 4.2 Quantitative Evaluation -- 4.3 Robustness to Additional Pathology -- 4.4 3D Visualization of Results -- 5 Conclusion -- References -- Region-Aware Deep Localization Framework for Cervical Vertebrae in X-Ray Images -- 1 Introduction -- 2 Data -- 3 Methodology -- 3.1 Localization Ground Truth -- 3.2 Network Architectures -- 3.3 Training -- 3.4 Region-Aware Term -- 3.5 Updated Loss Function -- 3.6 Experiments and Inference -- 4 Results and Discussions -- 5 Conclusion -- References -- Domain-Adversarial Neural Networks to Address the Appearance Variability of Histopathology Images -- 1 Introduction -- 2 Materials and Methods -- 2.1 Datasets -- 2.2 The Underlying CNN Architecture -- 2.3 Three Approaches to Handling Appearance Variability -- 2.4 Evaluation -- 3 Experiments and Results -- 4 Discussion and Conclusions -- References -- Accurate Lung Segmentation via Network-Wise Training of Convolutional Networks -- 1 Introduction -- 2 Methods -- 2.1 Lung Segmentation with Atrous Convolutions -- 2.2 Network-Wise Training of CNN -- 3 Computational Experiments -- 3.1 Performance Metrics -- 3.2 Quantatitive and Qualititive Results -- 4 Conclusion -- References -- Deep Residual Recurrent Neural Networks for Characterisation of Cardiac Cycle Phase from Echocardiograms -- 1 Introduction -- 2 Methods -- 2.1 Dataset.
2.2 Deep Residual Recurrent Neural Networks (RRNs) -- 3 Experiments -- 4 Results and Discussion -- 5 Conclusion and Future Works -- References -- Computationally Efficient Cardiac Views Projection Using 3D Convolutional Neural Networks -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Conclusion -- References -- Non-rigid Craniofacial 2D-3D Registration Using CNN-Based Regression -- 1 Introduction -- 2 Methods -- 2.1 Regression-Based 2D-3D Registration -- 2.2 CNN Based Regressor -- 3 Experiments -- 3.1 Qualitative Assessment -- 4 Conclusion -- References -- A Deep Level Set Method for Image Segmentation -- 1 Introduction -- 2 Methods -- 2.1 The Level Set Method -- 2.2 The Integrated FCN-Levelset Model -- 3 Experiments and Results -- 3.1 Data -- 3.2 Experiments -- 3.3 Results -- 4 Discussion -- References -- Context-Based Normalization of Histological Stains Using Deep Convolutional Features -- 1 Introduction -- 2 Method -- 2.1 Feature-Aware Normalization -- 2.2 Normalization by Denoising -- 3 Experiments -- 4 Discussion -- References -- Transitioning Between Convolutional and Fully Connected Layers in Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Inception Module -- 3.2 Transition Module -- 4 Experiment -- 5 Results -- 5.1 Experiment 1: Comparison with Regularizers -- 5.2 Experiment 2: Comparing Architectures -- 5.3 Experiment 3: BreaKHis -- 6 Conclusion -- References -- Quantifying the Impact of Type 2 Diabetes on Brain Perfusion Using Deep Neural Networks -- 1 Introduction -- 2 Materials -- 3 Methods -- 3.1 Compute Mean Gray Matter CBF per Anatomical Region -- 3.2 Identify candidate regions for further analysis -- 3.3 Estimate Candidate Region Association Using a DNN -- 4 Results -- 4.1 Performance Comparison of the Learning Models -- 4.2 Statistical Significance of the Proposed Model -- 5 Discussion -- 6 Conclusions.
References -- Multi-stage Diagnosis of Alzheimer's Disease with Incomplete Multimodal Data via Multi-task Deep Learning -- 1 Introduction -- 2 Method -- 2.1 Multi-task Learning -- 2.2 Multi-task Deep Learning for Incomplete Multimodal Data -- 3 Materials, Preprocessing and Feature Extraction -- 4 Results and Discussions -- 5 Conclusion -- References -- A Multi-scale CNN and Curriculum Learning Strategy for Mammogram Classification -- 1 Introduction -- 2 Multi-scale CNN with Curriculum Learning Strategy -- 3 Experiments -- 4 Conclusions -- References -- Analyzing Microscopic Images of Peripheral Blood Smear Using Deep Learning -- 1 Introduction -- 2 The Shonit’System for Analysis of Peripheral Blood Smears -- 3 Deep Learning Techniques for Analyzing PBS Images -- 3.1 Cell Extraction -- 3.2 Cell Classification -- 4 Experimental Results -- 5 Conclusion -- References -- AGNet: Attention-Guided Network for Surgical Tool Presence Detection -- 1 Introduction -- 2 Attention-Guided Network -- 2.1 Global Prediction Network -- 2.2 Local Prediction Network -- 3 Experiments -- 3.1 Datasets and Preprocessing -- 3.2 Training Procedure -- 3.3 Ablation Analysis -- 3.4 Comparison with the State-of-the-Arts -- 4 Conclusion -- References -- Pathological Pulmonary Lobe Segmentation from CT Images Using Progressive Holistically Nested Neural Networks and Random Walker -- 1 Introduction -- 2 Method -- 2.1 Lobar Boundary Segmentation -- 2.2 3D Random Walker -- 3 Experiments and Results -- 4 Conclusion -- References -- End-to-End Unsupervised Deformable Image Registration with a Convolutional Neural Network -- 1 Introduction -- 2 Method -- 3 Data -- 4 Experiments and Results -- 4.1 Registration of Handwritten Digits -- 4.2 Registration of Cardiac MRI -- 5 Discussion and Conclusion -- References.
Stain Colour Normalisation to Improve Mitosis Detection on Breast Histology Images -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Method -- 4.1 Patch Generation -- 4.2 CNN Architecture -- 4.3 Training and Testing Workflow -- 5 Results and Discussion -- 6 Conclusion -- References -- 3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Pancreas Localization -- 2.3 Patient-Specific Probabilistic Atlas Generation and Pancreas Segmentation -- 3 Experiments and Discussion -- References -- A Unified Framework for Tumor Proliferation Score Prediction in Breast Histopathology -- 1 Introduction -- 2 Methodology -- 2.1 Whole Slide Image Handling -- 2.2 Deep Convolutional Neural Networks Based Mitosis Detection -- 2.3 Tumor Proliferation Score Prediction -- 3 Results -- 3.1 Datasets -- 3.2 Experiments -- 4 Conclusion -- References -- Generalised Dice Overlap as a Deep Learning Loss Function for Highly Unbalanced Segmentations -- 1 Introduction -- 2 Methods -- 2.1 Loss Functions for Unbalanced Data -- 2.2 Deep Learning Framework -- 3 Experiments and Results -- 3.1 Experiments -- 3.2 2D Results -- 3.3 3D Results -- 4 Discussion -- References -- ssEMnet: Serial-Section Electron Microscopy Image Registration Using a Spatial Transformer Network with Learned Features -- 1 Introduction -- 2 Method -- 2.1 Feature Generation Using a Convolutional Autoencoder -- 2.2 Deformable Image Registration Using a Spatial Transformer Network -- 3 Results -- 4 Discussion and Conclusion -- References -- Fully Convolutional Regression Network for Accurate Detection of Measurement Points -- 1 Introduction -- 2 Related Work -- 3 Regressing Point Locations -- 3.1 Fully Convolutional Network with Center of Mass Layer -- 3.2 Convolutional Long Short-Term Memory for Temporal Consistency -- 4 Results.
5 Conclusion.
Record Nr. UNISA-996465975403316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support : Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, Proceedings / / edited by M. Jorge Cardoso, Tal Arbel, Gustavo Carneiro, Tanveer Syeda-Mahmood, João Manuel R.S. Tavares, Mehdi Moradi, Andrew Bradley, Hayit Greenspan, João Paulo Papa, Anant Madabhushi, Jacinto C. Nascimento, Jaime S. Cardoso, Vasileios Belagiannis, Zhi Lu
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support : Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, Proceedings / / edited by M. Jorge Cardoso, Tal Arbel, Gustavo Carneiro, Tanveer Syeda-Mahmood, João Manuel R.S. Tavares, Mehdi Moradi, Andrew Bradley, Hayit Greenspan, João Paulo Papa, Anant Madabhushi, Jacinto C. Nascimento, Jaime S. Cardoso, Vasileios Belagiannis, Zhi Lu
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XIX, 385 p. 169 illus.)
Disciplina 006.42
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Artificial intelligence
Health informatics
Bioinformatics
Logic design
Image Processing and Computer Vision
Artificial Intelligence
Health Informatics
Computational Biology/Bioinformatics
Logic Design
ISBN 3-319-67558-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Workshop Editors -- Preface DLMIA 2017 -- Organization -- Preface ML-CDS 2017 -- Organization -- Contents -- Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017 -- Simultaneous Multiple Surface Segmentation Using Deep Learning -- 1 Introduction -- 2 Method -- 3 Experiments -- 4 Results -- 5 Discussion and Conclusion -- References -- A Deep Residual Inception Network for HEp-2 Cell Classification -- Abstract -- 1 Introduction -- 2 Deep Residual Inception -- 2.1 Network Architecture -- 2.2 DRI Module -- 2.3 Network Training -- 3 Results -- 3.1 Dataset -- 3.2 Data Augmentation -- 3.3 Performance Analysis -- 3.4 Comparisons -- 4 Conclusion -- References -- Joint Segmentation of Multiple Thoracic Organs in CT Images with Two Collaborative Deep Architectures -- 1 Introduction -- 2 Method -- 2.1 SharpMask Feature Fusion Architecture and CRF Refinement -- 2.2 Learning Anatomical Constraints -- 3 Experiments -- 3.1 Dataset and Pre-processing -- 3.2 Training -- 3.3 Results -- 4 Conclusions -- References -- Accelerated Magnetic Resonance Imaging by Adversarial Neural Network -- 1 Introduction -- 2 Method -- 2.1 K-space -- 2.2 Objective -- 2.3 Network Architecture -- 3 Experimental Results -- 4 Conclusions -- References -- Left Atrium Segmentation in CT Volumes with Fully Convolutional Networks -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Preprocessing -- 3.2 Fully Convolutional Network -- 3.3 Shape Constraints -- 4 Experiments -- 5 Conclusion -- References -- 3D Randomized Connection Network with Graph-Based Inference -- 1 Introduction -- 2 Methodology -- 2.1 Convolutional LSTM and 3D Convolution -- 2.2 Randomized Connection Network -- 2.3 Graph-Based Inference -- 3 Experiment -- 4 Conclusion -- References -- Adversarial Training and Dilated Convolutions for Brain MRI Segmentation -- 1 Introduction.
2 Materials and Methods -- 2.1 Data -- 2.2 Network Architecture -- 2.3 Adversarial Training -- 3 Experiments and Results -- 3.1 Experiments -- 3.2 Evaluation -- 4 Discussion and Conclusions -- References -- CNNs Enable Accurate and Fast Segmentation of Drusen in Optical Coherence Tomography -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Data Preparation -- 3.2 Network Architecture and Training -- 3.3 Three Approaches to Drusen Segmentation -- 4 Experiments and Results -- 4.1 Cross-Validation Setup -- 4.2 Quantitative Evaluation -- 4.3 Robustness to Additional Pathology -- 4.4 3D Visualization of Results -- 5 Conclusion -- References -- Region-Aware Deep Localization Framework for Cervical Vertebrae in X-Ray Images -- 1 Introduction -- 2 Data -- 3 Methodology -- 3.1 Localization Ground Truth -- 3.2 Network Architectures -- 3.3 Training -- 3.4 Region-Aware Term -- 3.5 Updated Loss Function -- 3.6 Experiments and Inference -- 4 Results and Discussions -- 5 Conclusion -- References -- Domain-Adversarial Neural Networks to Address the Appearance Variability of Histopathology Images -- 1 Introduction -- 2 Materials and Methods -- 2.1 Datasets -- 2.2 The Underlying CNN Architecture -- 2.3 Three Approaches to Handling Appearance Variability -- 2.4 Evaluation -- 3 Experiments and Results -- 4 Discussion and Conclusions -- References -- Accurate Lung Segmentation via Network-Wise Training of Convolutional Networks -- 1 Introduction -- 2 Methods -- 2.1 Lung Segmentation with Atrous Convolutions -- 2.2 Network-Wise Training of CNN -- 3 Computational Experiments -- 3.1 Performance Metrics -- 3.2 Quantatitive and Qualititive Results -- 4 Conclusion -- References -- Deep Residual Recurrent Neural Networks for Characterisation of Cardiac Cycle Phase from Echocardiograms -- 1 Introduction -- 2 Methods -- 2.1 Dataset.
2.2 Deep Residual Recurrent Neural Networks (RRNs) -- 3 Experiments -- 4 Results and Discussion -- 5 Conclusion and Future Works -- References -- Computationally Efficient Cardiac Views Projection Using 3D Convolutional Neural Networks -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Conclusion -- References -- Non-rigid Craniofacial 2D-3D Registration Using CNN-Based Regression -- 1 Introduction -- 2 Methods -- 2.1 Regression-Based 2D-3D Registration -- 2.2 CNN Based Regressor -- 3 Experiments -- 3.1 Qualitative Assessment -- 4 Conclusion -- References -- A Deep Level Set Method for Image Segmentation -- 1 Introduction -- 2 Methods -- 2.1 The Level Set Method -- 2.2 The Integrated FCN-Levelset Model -- 3 Experiments and Results -- 3.1 Data -- 3.2 Experiments -- 3.3 Results -- 4 Discussion -- References -- Context-Based Normalization of Histological Stains Using Deep Convolutional Features -- 1 Introduction -- 2 Method -- 2.1 Feature-Aware Normalization -- 2.2 Normalization by Denoising -- 3 Experiments -- 4 Discussion -- References -- Transitioning Between Convolutional and Fully Connected Layers in Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Inception Module -- 3.2 Transition Module -- 4 Experiment -- 5 Results -- 5.1 Experiment 1: Comparison with Regularizers -- 5.2 Experiment 2: Comparing Architectures -- 5.3 Experiment 3: BreaKHis -- 6 Conclusion -- References -- Quantifying the Impact of Type 2 Diabetes on Brain Perfusion Using Deep Neural Networks -- 1 Introduction -- 2 Materials -- 3 Methods -- 3.1 Compute Mean Gray Matter CBF per Anatomical Region -- 3.2 Identify candidate regions for further analysis -- 3.3 Estimate Candidate Region Association Using a DNN -- 4 Results -- 4.1 Performance Comparison of the Learning Models -- 4.2 Statistical Significance of the Proposed Model -- 5 Discussion -- 6 Conclusions.
References -- Multi-stage Diagnosis of Alzheimer's Disease with Incomplete Multimodal Data via Multi-task Deep Learning -- 1 Introduction -- 2 Method -- 2.1 Multi-task Learning -- 2.2 Multi-task Deep Learning for Incomplete Multimodal Data -- 3 Materials, Preprocessing and Feature Extraction -- 4 Results and Discussions -- 5 Conclusion -- References -- A Multi-scale CNN and Curriculum Learning Strategy for Mammogram Classification -- 1 Introduction -- 2 Multi-scale CNN with Curriculum Learning Strategy -- 3 Experiments -- 4 Conclusions -- References -- Analyzing Microscopic Images of Peripheral Blood Smear Using Deep Learning -- 1 Introduction -- 2 The Shonit’System for Analysis of Peripheral Blood Smears -- 3 Deep Learning Techniques for Analyzing PBS Images -- 3.1 Cell Extraction -- 3.2 Cell Classification -- 4 Experimental Results -- 5 Conclusion -- References -- AGNet: Attention-Guided Network for Surgical Tool Presence Detection -- 1 Introduction -- 2 Attention-Guided Network -- 2.1 Global Prediction Network -- 2.2 Local Prediction Network -- 3 Experiments -- 3.1 Datasets and Preprocessing -- 3.2 Training Procedure -- 3.3 Ablation Analysis -- 3.4 Comparison with the State-of-the-Arts -- 4 Conclusion -- References -- Pathological Pulmonary Lobe Segmentation from CT Images Using Progressive Holistically Nested Neural Networks and Random Walker -- 1 Introduction -- 2 Method -- 2.1 Lobar Boundary Segmentation -- 2.2 3D Random Walker -- 3 Experiments and Results -- 4 Conclusion -- References -- End-to-End Unsupervised Deformable Image Registration with a Convolutional Neural Network -- 1 Introduction -- 2 Method -- 3 Data -- 4 Experiments and Results -- 4.1 Registration of Handwritten Digits -- 4.2 Registration of Cardiac MRI -- 5 Discussion and Conclusion -- References.
Stain Colour Normalisation to Improve Mitosis Detection on Breast Histology Images -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Method -- 4.1 Patch Generation -- 4.2 CNN Architecture -- 4.3 Training and Testing Workflow -- 5 Results and Discussion -- 6 Conclusion -- References -- 3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Pancreas Localization -- 2.3 Patient-Specific Probabilistic Atlas Generation and Pancreas Segmentation -- 3 Experiments and Discussion -- References -- A Unified Framework for Tumor Proliferation Score Prediction in Breast Histopathology -- 1 Introduction -- 2 Methodology -- 2.1 Whole Slide Image Handling -- 2.2 Deep Convolutional Neural Networks Based Mitosis Detection -- 2.3 Tumor Proliferation Score Prediction -- 3 Results -- 3.1 Datasets -- 3.2 Experiments -- 4 Conclusion -- References -- Generalised Dice Overlap as a Deep Learning Loss Function for Highly Unbalanced Segmentations -- 1 Introduction -- 2 Methods -- 2.1 Loss Functions for Unbalanced Data -- 2.2 Deep Learning Framework -- 3 Experiments and Results -- 3.1 Experiments -- 3.2 2D Results -- 3.3 3D Results -- 4 Discussion -- References -- ssEMnet: Serial-Section Electron Microscopy Image Registration Using a Spatial Transformer Network with Learned Features -- 1 Introduction -- 2 Method -- 2.1 Feature Generation Using a Convolutional Autoencoder -- 2.2 Deformable Image Registration Using a Spatial Transformer Network -- 3 Results -- 4 Discussion and Conclusion -- References -- Fully Convolutional Regression Network for Accurate Detection of Measurement Points -- 1 Introduction -- 2 Related Work -- 3 Regressing Point Locations -- 3.1 Fully Convolutional Network with Center of Mass Layer -- 3.2 Convolutional Long Short-Term Memory for Temporal Consistency -- 4 Results.
5 Conclusion.
Record Nr. UNINA-9910484561103321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Pattern Recognition and Image Analysis [[electronic resource] ] : 7th Iberian Conference, IbPRIA 2015, Santiago de Compostela, Spain, June 17-19, 2015, Proceedings / / edited by Roberto Paredes, Jaime S. Cardoso, Xosé M. Pardo
Pattern Recognition and Image Analysis [[electronic resource] ] : 7th Iberian Conference, IbPRIA 2015, Santiago de Compostela, Spain, June 17-19, 2015, Proceedings / / edited by Roberto Paredes, Jaime S. Cardoso, Xosé M. Pardo
Edizione [1st ed. 2015.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
Descrizione fisica 1 online resource (XVI, 753 p. 275 illus.)
Disciplina 006.42
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Pattern recognition
Optical data processing
Natural language processing (Computer science)
Computer graphics
Artificial intelligence
Pattern Recognition
Computer Imaging, Vision, Pattern Recognition and Graphics
Image Processing and Computer Vision
Natural Language Processing (NLP)
Computer Graphics
Artificial Intelligence
ISBN 3-319-19390-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Pattern Recognition and Machine Learning -- Spatiotemporal Stacked Sequential Learning for Pedestrian Detection -- Social Signaling Descriptor for Group Behaviour Analysis -- A New Smoothing Method for Lexicon-Based Handwritten Text Keyword Spotting -- Empirical Evaluation of Different Feature Representations for Social Circles Detection -- Source-Target-Source Classification Using Stacked Denoising Autoencoders -- On the Impact of Distance Metrics in Instance-Based Learning Algorithms -- Multi-class Boosting for Imbalanced Data -- Computer Vision -- Object Discovery Using CNN Features in Egocentric Videos -- Prototype Generation on Structural Data Using Dissimilarity Space Representation: A Case of Study -- Estimation and Tracking of Partial Planar Templates to Improve VSLAM -- Human Centered Scene Understanding Based on 3D Long-Term Tracking Data -- Fast Head Pose Estimation for Human-Computer Interaction -- Structured Light System Calibration for Perception in Underwater Tanks -- Dense 3D SLAM in Dynamic Scenes Using Kinect -- Scene Recognition Invariant to Symmetrical Reflections and Illumination Conditions in Robotics -- System for Medical Mask Detection in the Operating Room Through Facial Attributes -- Image and Signal Processing -- New Method for Obtaining Optimal Polygonal Approximations -- Noise Decomposition Using Polynomial Approximation -- Color Correction for Image Stitching by Monotone Cubic Spline Interpolation -- Structured Output Prediction with Hierarchical Loss Functions for Seafloor Imagery Taxonomic Categorization -- Escaping Path Approach with Extended Neighborhood for Speckle Noise Reduction -- Adaptive Line Matching for Low-Textured Images -- Unsupervised Approximation of Digital Planar Curves -- On the Modification of Binarization Algorithms to Retain Grayscale Information for Handwritten Text Recognition -- Applications -- Improving the Minimum Description Length Inference of Phrase-Based Translation Models -- A Kinect-Based System to Assess Lymphedema Impairments in Breast Cancer Patients -- Arabic Writer Identification Using Local Binary Patterns (LBP) of Handwritten Fragments -- A Fuzzy C-Means Algorithm for Fingerprint Segmentation -- Word-Graph Based Applications for Handwriting Documents: Impact of Word-Graph Size on Their Performances -- Temporal Segmentation of Digital Colposcopies -- Goal-Driven Phenotyping Through Spectral Imaging for Grape Aromatic Ripeness Assessment -- Medical Image -- Robust 3D Active Shape Model for the Segmentation of the Left Ventricle in MRI -- Kernel-Based Feature Relevance Analysis for ECG Beat Classification -- Spatial-Dependent Similarity Metric Supporting Multi-atlas MRI Segmentation -- Color Detection in Dermoscopy Images Based on Scarce Annotations -- Pattern Recognition and Machine Learning -- Spectral Clustering Using Friendship Path Similarity -- R-Clustering for Egocentric Video Segmentation -- Applying Basic Features from Sentiment Analysis for Automatic Irony Detection -- Exploiting the Bin-Class Histograms for Feature Selection on Discrete Data -- Time-Series Prediction Based on Kernel Adaptive Filtering with Cyclostationary Codebooks -- Latent Topic Encoding for Content-Based Retrieval -- Dissimilarity-Based Learning from Imbalanced Data with Small Disjuncts and Noise -- Binary and Multi-class Parkinsonian Disorders Classification Using Support Vector Machines -- Peripheral Nerve Segmentation Using Speckle Removal and Bayesian Shape Models -- Measuring Scene Detection Performance -- Threshold of Graph-Based Volumetric Segmentation -- Brain Neural Data Analysis with Feature Space Defined by Descriptive Statistics -- Extremely Overlapping Vehicle Counting -- Sentence Clustering Using Continuous Vector Space Representation -- Online Learning of Stochastic Bi-automaton to Model Dialogues -- Single-Channel Separation Between Stationary and Non-stationary Signals Using Relevant Information -- Computer Vision -- A New Trajectory Based Motion Segmentation Benchmark Dataset (UdG-MS15) -- Escritoire: A Multi-touch Desk with e-Pen Input for Capture, Management and Multimodal Interactive Transcription of Handwritten Documents -- Person Enrollment by Face-Gait Fusion -- Homographic Class Template for Logo Localization and Recognition -- Multimodal Object Recognition Using Random Clustering Trees -- Videogrammetry System for Wind Turbine Vibration Monitoring -- Canonical Views for Scene Recognition in Mobile Robotics -- Crater Detection in Multi-ring Basins of Mercury -- Iterative Versus Voting Method to Reach Consensus Given Multiple Correspondences of Two Sets -- Extracting Categories by Hierarchical Clustering Using Global Relational Features -- A Calibration Algorithm for Multi-camera Visual Surveillance Systems Based on Single-View Metrology -- 3D-Guided Multiscale Sliding Window for Pedestrian Detection -- A Feature-Based Gaze Estimation Algorithm for Natural Light Scenarios -- Image and Signal Processing -- Fast Simple Linear Iterative Clustering by Early Candidate Cluster Elimination -- Pectoral Muscle Segmentation in Mammograms Based on Cartoon-Texture Decomposition -- PPG Beat Reconstruction Based on Shape Models and Probabilistic Templates for Signals Acquired with Conventional Smartphones -- Peripheral Nerves Segmentation in Ultrasound Images Using Non-linear Wavelets and Gaussian Processes -- Improving Diffusion Tensor Estimation Using Adaptive and Optimized Filtering Based on Local Similarity -- Dimension Reduction of Hyperspectral Image with Rare Event Preserving -- Applications -- Clustering of Strokes from Pen-Based Music Notation: An Experimental Study -- Image Analysis-Based Automatic Detection of Transmission Towers Using Aerial Imagery -- A Sliding Window Framework for Word Spotting Based on Word Attributes -- Combining Statistical and Semantic Knowledge for Sarcasm Detection in Online Dialogues -- Estimating Fuel Consumption from GPS Data -- A Bag-of-phonemes Model for Homeplace Classification of Mandarin Speakers -- A Gaussian Process Emulator for Estimating the Volume of Tissue Activated During Deep Brain Stimulation -- Genetic Seam Carving: A Genetic Algorithm Approach for Content-Aware Image Retargeting -- Analysis of Expressiveness of Portuguese Sign Language Speakers -- Automatic Eye Localization; Multi-block LBP vs. Pyramidal LBP Three-Levels Image Decomposition for Eye Visual Appearance Description -- Clinical Evaluation of an Automatic Method for Segmentation and Characterization of the Thoracic Aorta with and Without Aneurysm Patients -- Combined MPEG7 Color Descriptors for Image Classification: Bypassing the Training Phase -- A Multi-platform Graphical Software for Determining Reproductive Parameters in Fishes Using Histological Image Analysis.
Record Nr. UNISA-996198525203316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
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Pattern Recognition and Image Analysis : 7th Iberian Conference, IbPRIA 2015, Santiago de Compostela, Spain, June 17-19, 2015, Proceedings / / edited by Roberto Paredes, Jaime S. Cardoso, Xosé M. Pardo
Pattern Recognition and Image Analysis : 7th Iberian Conference, IbPRIA 2015, Santiago de Compostela, Spain, June 17-19, 2015, Proceedings / / edited by Roberto Paredes, Jaime S. Cardoso, Xosé M. Pardo
Edizione [1st ed. 2015.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
Descrizione fisica 1 online resource (XVI, 753 p. 275 illus.)
Disciplina 006.42
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Pattern recognition
Optical data processing
Natural language processing (Computer science)
Computer graphics
Artificial intelligence
Pattern Recognition
Computer Imaging, Vision, Pattern Recognition and Graphics
Image Processing and Computer Vision
Natural Language Processing (NLP)
Computer Graphics
Artificial Intelligence
ISBN 3-319-19390-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Pattern Recognition and Machine Learning -- Spatiotemporal Stacked Sequential Learning for Pedestrian Detection -- Social Signaling Descriptor for Group Behaviour Analysis -- A New Smoothing Method for Lexicon-Based Handwritten Text Keyword Spotting -- Empirical Evaluation of Different Feature Representations for Social Circles Detection -- Source-Target-Source Classification Using Stacked Denoising Autoencoders -- On the Impact of Distance Metrics in Instance-Based Learning Algorithms -- Multi-class Boosting for Imbalanced Data -- Computer Vision -- Object Discovery Using CNN Features in Egocentric Videos -- Prototype Generation on Structural Data Using Dissimilarity Space Representation: A Case of Study -- Estimation and Tracking of Partial Planar Templates to Improve VSLAM -- Human Centered Scene Understanding Based on 3D Long-Term Tracking Data -- Fast Head Pose Estimation for Human-Computer Interaction -- Structured Light System Calibration for Perception in Underwater Tanks -- Dense 3D SLAM in Dynamic Scenes Using Kinect -- Scene Recognition Invariant to Symmetrical Reflections and Illumination Conditions in Robotics -- System for Medical Mask Detection in the Operating Room Through Facial Attributes -- Image and Signal Processing -- New Method for Obtaining Optimal Polygonal Approximations -- Noise Decomposition Using Polynomial Approximation -- Color Correction for Image Stitching by Monotone Cubic Spline Interpolation -- Structured Output Prediction with Hierarchical Loss Functions for Seafloor Imagery Taxonomic Categorization -- Escaping Path Approach with Extended Neighborhood for Speckle Noise Reduction -- Adaptive Line Matching for Low-Textured Images -- Unsupervised Approximation of Digital Planar Curves -- On the Modification of Binarization Algorithms to Retain Grayscale Information for Handwritten Text Recognition -- Applications -- Improving the Minimum Description Length Inference of Phrase-Based Translation Models -- A Kinect-Based System to Assess Lymphedema Impairments in Breast Cancer Patients -- Arabic Writer Identification Using Local Binary Patterns (LBP) of Handwritten Fragments -- A Fuzzy C-Means Algorithm for Fingerprint Segmentation -- Word-Graph Based Applications for Handwriting Documents: Impact of Word-Graph Size on Their Performances -- Temporal Segmentation of Digital Colposcopies -- Goal-Driven Phenotyping Through Spectral Imaging for Grape Aromatic Ripeness Assessment -- Medical Image -- Robust 3D Active Shape Model for the Segmentation of the Left Ventricle in MRI -- Kernel-Based Feature Relevance Analysis for ECG Beat Classification -- Spatial-Dependent Similarity Metric Supporting Multi-atlas MRI Segmentation -- Color Detection in Dermoscopy Images Based on Scarce Annotations -- Pattern Recognition and Machine Learning -- Spectral Clustering Using Friendship Path Similarity -- R-Clustering for Egocentric Video Segmentation -- Applying Basic Features from Sentiment Analysis for Automatic Irony Detection -- Exploiting the Bin-Class Histograms for Feature Selection on Discrete Data -- Time-Series Prediction Based on Kernel Adaptive Filtering with Cyclostationary Codebooks -- Latent Topic Encoding for Content-Based Retrieval -- Dissimilarity-Based Learning from Imbalanced Data with Small Disjuncts and Noise -- Binary and Multi-class Parkinsonian Disorders Classification Using Support Vector Machines -- Peripheral Nerve Segmentation Using Speckle Removal and Bayesian Shape Models -- Measuring Scene Detection Performance -- Threshold of Graph-Based Volumetric Segmentation -- Brain Neural Data Analysis with Feature Space Defined by Descriptive Statistics -- Extremely Overlapping Vehicle Counting -- Sentence Clustering Using Continuous Vector Space Representation -- Online Learning of Stochastic Bi-automaton to Model Dialogues -- Single-Channel Separation Between Stationary and Non-stationary Signals Using Relevant Information -- Computer Vision -- A New Trajectory Based Motion Segmentation Benchmark Dataset (UdG-MS15) -- Escritoire: A Multi-touch Desk with e-Pen Input for Capture, Management and Multimodal Interactive Transcription of Handwritten Documents -- Person Enrollment by Face-Gait Fusion -- Homographic Class Template for Logo Localization and Recognition -- Multimodal Object Recognition Using Random Clustering Trees -- Videogrammetry System for Wind Turbine Vibration Monitoring -- Canonical Views for Scene Recognition in Mobile Robotics -- Crater Detection in Multi-ring Basins of Mercury -- Iterative Versus Voting Method to Reach Consensus Given Multiple Correspondences of Two Sets -- Extracting Categories by Hierarchical Clustering Using Global Relational Features -- A Calibration Algorithm for Multi-camera Visual Surveillance Systems Based on Single-View Metrology -- 3D-Guided Multiscale Sliding Window for Pedestrian Detection -- A Feature-Based Gaze Estimation Algorithm for Natural Light Scenarios -- Image and Signal Processing -- Fast Simple Linear Iterative Clustering by Early Candidate Cluster Elimination -- Pectoral Muscle Segmentation in Mammograms Based on Cartoon-Texture Decomposition -- PPG Beat Reconstruction Based on Shape Models and Probabilistic Templates for Signals Acquired with Conventional Smartphones -- Peripheral Nerves Segmentation in Ultrasound Images Using Non-linear Wavelets and Gaussian Processes -- Improving Diffusion Tensor Estimation Using Adaptive and Optimized Filtering Based on Local Similarity -- Dimension Reduction of Hyperspectral Image with Rare Event Preserving -- Applications -- Clustering of Strokes from Pen-Based Music Notation: An Experimental Study -- Image Analysis-Based Automatic Detection of Transmission Towers Using Aerial Imagery -- A Sliding Window Framework for Word Spotting Based on Word Attributes -- Combining Statistical and Semantic Knowledge for Sarcasm Detection in Online Dialogues -- Estimating Fuel Consumption from GPS Data -- A Bag-of-phonemes Model for Homeplace Classification of Mandarin Speakers -- A Gaussian Process Emulator for Estimating the Volume of Tissue Activated During Deep Brain Stimulation -- Genetic Seam Carving: A Genetic Algorithm Approach for Content-Aware Image Retargeting -- Analysis of Expressiveness of Portuguese Sign Language Speakers -- Automatic Eye Localization; Multi-block LBP vs. Pyramidal LBP Three-Levels Image Decomposition for Eye Visual Appearance Description -- Clinical Evaluation of an Automatic Method for Segmentation and Characterization of the Thoracic Aorta with and Without Aneurysm Patients -- Combined MPEG7 Color Descriptors for Image Classification: Bypassing the Training Phase -- A Multi-platform Graphical Software for Determining Reproductive Parameters in Fishes Using Histological Image Analysis.
Record Nr. UNINA-9910484764403321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
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