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Autor Suzuki, Kenji |
Documentos disponibles escritos por este autor (4)
Crear una solicitud de compra Refinar búsquedaArtificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging / Suzuki, Kenji ; Chen, Yisong
TÃtulo : Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging Tipo de documento: documento electrónico Autores: Suzuki, Kenji, ; Chen, Yisong, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2018 Número de páginas: XXI, 387 p. 140 ilustraciones, 96 ilustraciones en color. ISBN/ISSN/DL: 978-3-319-68843-5 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Inteligencia Computacional IngenierÃa Biomédica Inteligencia artificial RadiologÃa IngenierÃa Biomédica y BioingenierÃa Clasificación: 006.3 Resumen: Este libro ofrece la primera descripción general completa de las tecnologÃas de inteligencia artificial (IA) en sistemas de apoyo a la toma de decisiones para el diagnóstico basado en imágenes médicas, y presenta conocimientos de vanguardia de trece grupos de investigación lÃderes de todo el mundo. Las imágenes médicas ofrecen información esencial sobre la condición médica de los pacientes y pistas sobre las causas de sus sÃntomas y enfermedades. Sin embargo, las modalidades de imágenes modernas también producen una gran cantidad de imágenes que los médicos deben interpretar con precisión. Esto puede provocar una "sobrecarga de información" para los médicos y complicar su toma de decisiones. Como tal, los sistemas inteligentes de apoyo a las decisiones se han convertido en un elemento vital en el diagnóstico y tratamiento basado en imágenes médicas. Al presentar amplia información sobre este creciente campo de la IA, el libro ofrece una valiosa guÃa de referencia para profesores, estudiantes, investigadores y profesionales que quieran conocer los desarrollos y avances más recientes en este campo. Tipo de medio : Computadora Summary : This book offers the first comprehensive overview of artificial intelligence (AI) technologies in decision support systems for diagnosis based on medical images, presenting cutting-edge insights from thirteen leading research groups around the world. Medical imaging offers essential information on patients' medical condition, and clues to causes of their symptoms and diseases. Modern imaging modalities, however, also produce a large number of images that physicians have to accurately interpret. This can lead to an "information overload" for physicians, and can complicate their decision-making. As such, intelligent decision support systems have become a vital element in medical-image-based diagnosis and treatment. Presenting extensive information on this growing field of AI, the book offers a valuable reference guide for professors, students, researchers and professionals who want to learn about the most recent developments and advances in the field. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging [documento electrónico] / Suzuki, Kenji, ; Chen, Yisong, . - 1 ed. . - [s.l.] : Springer, 2018 . - XXI, 387 p. 140 ilustraciones, 96 ilustraciones en color.
ISBN : 978-3-319-68843-5
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Inteligencia Computacional IngenierÃa Biomédica Inteligencia artificial RadiologÃa IngenierÃa Biomédica y BioingenierÃa Clasificación: 006.3 Resumen: Este libro ofrece la primera descripción general completa de las tecnologÃas de inteligencia artificial (IA) en sistemas de apoyo a la toma de decisiones para el diagnóstico basado en imágenes médicas, y presenta conocimientos de vanguardia de trece grupos de investigación lÃderes de todo el mundo. Las imágenes médicas ofrecen información esencial sobre la condición médica de los pacientes y pistas sobre las causas de sus sÃntomas y enfermedades. Sin embargo, las modalidades de imágenes modernas también producen una gran cantidad de imágenes que los médicos deben interpretar con precisión. Esto puede provocar una "sobrecarga de información" para los médicos y complicar su toma de decisiones. Como tal, los sistemas inteligentes de apoyo a las decisiones se han convertido en un elemento vital en el diagnóstico y tratamiento basado en imágenes médicas. Al presentar amplia información sobre este creciente campo de la IA, el libro ofrece una valiosa guÃa de referencia para profesores, estudiantes, investigadores y profesionales que quieran conocer los desarrollos y avances más recientes en este campo. Tipo de medio : Computadora Summary : This book offers the first comprehensive overview of artificial intelligence (AI) technologies in decision support systems for diagnosis based on medical images, presenting cutting-edge insights from thirteen leading research groups around the world. Medical imaging offers essential information on patients' medical condition, and clues to causes of their symptoms and diseases. Modern imaging modalities, however, also produce a large number of images that physicians have to accurately interpret. This can lead to an "information overload" for physicians, and can complicate their decision-making. As such, intelligent decision support systems have become a vital element in medical-image-based diagnosis and treatment. Presenting extensive information on this growing field of AI, the book offers a valuable reference guide for professors, students, researchers and professionals who want to learn about the most recent developments and advances in the field. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support : Second International Workshop, iMIMIC 2019, and 9th International Workshop, ML-CDS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings Tipo de documento: documento electrónico Autores: Suzuki, Kenji, ; Reyes, Mauricio, ; Syeda-Mahmood, Tanveer, ; Konukoglu, Ender, ; Glocker, Ben, ; Wiest, Roland, ; Gur, Yaniv, ; Greenspan, Hayit, ; Madabhushi, Anant, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2019 Número de páginas: XVI, 93 p. 40 ilustraciones, 35 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-33850-3 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Inteligencia artificial Informática de la Salud Lenguajes formales y teorÃa de los autómatas Visión por computador TeorÃa de las máquinas Informática Médica Clasificación: 006.3 Resumen: Este libro constituye las actas conjuntas arbitradas del Segundo Taller Internacional sobre Interpretabilidad de la Inteligencia Artificial en Computación de Imágenes Médicas, iMIMIC 2019, y el 9º Taller Internacional sobre Aprendizaje Multimodal para el Apoyo a la Decisión ClÃnica, ML-CDS 2019, celebrado en conjunto con el 22º Taller Internacional Conferencia sobre imágenes médicas e intervención asistida por computadora, MICCAI 2019, en Shenzhen, China, en octubre de 2019. Los 7 artÃculos completos presentados en iMIMIC 2019 y los 3 artÃculos completos presentados en ML-CDS 2019 fueron cuidadosamente revisados ​​y seleccionados entre 10 presentaciones para iMIMIC y numerosas presentaciones a ML-CDS. Los artÃculos de iMIMIC se centran en presentar los desafÃos y oportunidades relacionados con el tema de la interpretabilidad de los sistemas de aprendizaje automático en el contexto de las imágenes médicas y la intervención asistida por computadora. Los artÃculos de ML-CDS analizan el aprendizaje automático en conjuntos de datos multimodales para apoyar la toma de decisiones clÃnicas y la planificación del tratamiento. . Nota de contenido: Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC 2019) -- Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimer's disease classification -- UBS: A Dimension-Agnostic Metric for Concept Vector Interpretability Applied to Radiomics -- Generation of Multimodal Justification Using Visual Word Constraint Model for Explainable Computer-Aided Diagnosis -- Incorporating Task-Specific Structural Knowledge into CNNs for Brain Midline Shift Detection -- Guideline-based Additive Explanation for Computer-Aided Diagnosis of Lung Nodules -- Deep neural network or dermatologist? -- Towards Interpretability of Segmentation Networks by analyzing DeepDreams -- 9th International Workshop on Multimodal Learning for Clinical Decision Support (ML-CDS 2019) -- Towards Automatic Diagnosis from Multi-modal Medical Data -- Deep Learning based Multi-Modal Registration for Retinal Imaging.-Automated Enriched Medical Concept Generation for Chest X-ray Images. Tipo de medio : Computadora Summary : This book constitutes the refereed joint proceedings of the Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2019, and the 9th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 7 full papers presented at iMIMIC 2019 and the 3 full papers presented at ML-CDS 2019 were carefully reviewed and selected from 10 submissions to iMIMIC and numerous submissions to ML-CDS. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. . Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support : Second International Workshop, iMIMIC 2019, and 9th International Workshop, ML-CDS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings [documento electrónico] / Suzuki, Kenji, ; Reyes, Mauricio, ; Syeda-Mahmood, Tanveer, ; Konukoglu, Ender, ; Glocker, Ben, ; Wiest, Roland, ; Gur, Yaniv, ; Greenspan, Hayit, ; Madabhushi, Anant, . - 1 ed. . - [s.l.] : Springer, 2019 . - XVI, 93 p. 40 ilustraciones, 35 ilustraciones en color.
ISBN : 978-3-030-33850-3
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Inteligencia artificial Informática de la Salud Lenguajes formales y teorÃa de los autómatas Visión por computador TeorÃa de las máquinas Informática Médica Clasificación: 006.3 Resumen: Este libro constituye las actas conjuntas arbitradas del Segundo Taller Internacional sobre Interpretabilidad de la Inteligencia Artificial en Computación de Imágenes Médicas, iMIMIC 2019, y el 9º Taller Internacional sobre Aprendizaje Multimodal para el Apoyo a la Decisión ClÃnica, ML-CDS 2019, celebrado en conjunto con el 22º Taller Internacional Conferencia sobre imágenes médicas e intervención asistida por computadora, MICCAI 2019, en Shenzhen, China, en octubre de 2019. Los 7 artÃculos completos presentados en iMIMIC 2019 y los 3 artÃculos completos presentados en ML-CDS 2019 fueron cuidadosamente revisados ​​y seleccionados entre 10 presentaciones para iMIMIC y numerosas presentaciones a ML-CDS. Los artÃculos de iMIMIC se centran en presentar los desafÃos y oportunidades relacionados con el tema de la interpretabilidad de los sistemas de aprendizaje automático en el contexto de las imágenes médicas y la intervención asistida por computadora. Los artÃculos de ML-CDS analizan el aprendizaje automático en conjuntos de datos multimodales para apoyar la toma de decisiones clÃnicas y la planificación del tratamiento. . Nota de contenido: Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC 2019) -- Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimer's disease classification -- UBS: A Dimension-Agnostic Metric for Concept Vector Interpretability Applied to Radiomics -- Generation of Multimodal Justification Using Visual Word Constraint Model for Explainable Computer-Aided Diagnosis -- Incorporating Task-Specific Structural Knowledge into CNNs for Brain Midline Shift Detection -- Guideline-based Additive Explanation for Computer-Aided Diagnosis of Lung Nodules -- Deep neural network or dermatologist? -- Towards Interpretability of Segmentation Networks by analyzing DeepDreams -- 9th International Workshop on Multimodal Learning for Clinical Decision Support (ML-CDS 2019) -- Towards Automatic Diagnosis from Multi-modal Medical Data -- Deep Learning based Multi-Modal Registration for Retinal Imaging.-Automated Enriched Medical Concept Generation for Chest X-ray Images. Tipo de medio : Computadora Summary : This book constitutes the refereed joint proceedings of the Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2019, and the 9th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 7 full papers presented at iMIMIC 2019 and the 3 full papers presented at ML-CDS 2019 were carefully reviewed and selected from 10 submissions to iMIMIC and numerous submissions to ML-CDS. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. . Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Machine Learning in Medical Imaging : 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Proceedings Tipo de documento: documento electrónico Autores: Wang, Qian, ; Shi, Yinghuan, ; Suk, Heung-Il, ; Suzuki, Kenji, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2017 Número de páginas: XV, 391 p. 134 ilustraciones ISBN/ISSN/DL: 978-3-319-67389-9 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Visión por computador IngenierÃa de software Informática Médica Procesamiento de datos Inteligencia artificial Informática de la Salud MinerÃa de datos y descubrimiento de conocimientos Clasificación: 006.37 Resumen: Este libro constituye las actas arbitradas del 8º Taller Internacional sobre Aprendizaje Automático en Imágenes Médicas, MLMI 2017, celebrado junto con MICCAI 2017, en la ciudad de Quebec, QC, Canadá, en septiembre de 2017. Los 44 artÃculos completos presentados en este volumen fueron cuidadosamente revisado y seleccionado entre 63 presentaciones. El objetivo principal de este taller es ayudar a avanzar en la investigación cientÃfica dentro del amplio campo del aprendizaje automático en imágenes médicas. El taller se centra en las principales tendencias y desafÃos en esta área, y presenta trabajos destinados a identificar nuevas técnicas de vanguardia y su uso en imágenes médicas. Nota de contenido: From Large to Small Organ Segmentation in CT Using Regional Context -- Motion Corruption Detection in Breast DCE-MRI -- Detection and Localization of Drosophila Egg Chambers in Microscopy Images -- Growing a Random Forest with Fuzzy Spatial Features for Fully Automatic Artery-specific Coronary Calcium Scoring -- Atlas of Classifiers for Brain MRI Segmentation -- Dictionary Learning and Sparse Coding-based Denoising for High-Resolution Task Functional Connectivity MRI Analysis -- Yet Another ADNI Machine Learning Paper? Paving The Way Towards Fully-reproducible Research on Classification of Alzheimer's Disease -- Multi-Factorial Age Estimation from Skeletal and Dental MRI Volumes -- Automatic Classification of Proximal Femur Fractures Based on Attention Models -- Joint Supervoxel Classification Forest for Weakly-Supervised Organ Segmentation -- Accurate and Consistent Hippocampus Segmentation Through Convolutional LSTM and View Ensemble -- STAR: Spatio-Temporal Architecture for Super-Resolution inLow-Dose CT Perfusion -- Classification of Alzheimer's Disease by Cascaded Convolutional Neural Networks Using PET Images -- Finding Dense Supervoxel Correspondence of Cone-Beam Computed Tomography Images -- Multi-Scale Volumetric ConvNet with Nested Residual Connections for Segmentation of Anterior Cranial Base -- Feature Learning and Fusion of Multimodality Neuroimaging and Genetic Data for Multi-Status Dementia Diagnosis -- 3D Convolutional Neural Networks with Graph Refinement for Airway Segmentation Using Incomplete Data Labels -- Efficient Groupwise Registration for Brain MRI by Fast Initialization -- Sparse Multi-View Task-centralized Learning for ASD Diagnosis -- Inter-Subject Similarity Guided Brain Network Modelling for MCI Diagnosis -- Scalable and Fault Tolerant Platform for Distributed Learning on Private Medical Data -- Triple-Crossing 2.5D Convolutional Neural Network for Detecting Neuronal Arbours in 3D Microscopic Images -- Longitudinally-Consistent Parcellation of Infant Population Cortical Surfaces Based on Functional Connectivity -- Gradient Boosted Trees for Corrective Learning -- Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis -- A Point Says a Lot: An Interactive Segmentation Method for MR Prostate via One-Point Labeling -- Collage CNN for Renal Cell Carcinoma Detection from CT -- Aggregating Deep Convolutional Features for Melanoma Recognition in Dermoscopy Images -- Localizing Cardiac Structures in Fetal Heart Ultrasound Video -- Deformable Registration Through Learning of Context-Specific Metric Aggregation -- Segmentation of Craniomaxillofacial Bony Structures from MRI with a 3D Deep-learning Based Cascade Framework -- 3D U-net with Multi-Level Deep Supervision: Fully Automatic Segmentation of Proximal Femur in 3D MR Images -- Indecisive Trees for Classification and Prediction of Knee Osteoarthritis -- Whole Brain Segmentation and Labeling from CT using synthetic MR Images -- Structural Connectivity Guided SparseEffective Connectivity for MCI Identification -- Fusion of High-order and Low-order Effective Connectivity Networks for MCI Classification -- Novel Effective Connectivity Network Inference for MCI Identification -- Reconstruction of Thin-Slice Medical Images Using Generative Adversarial Network -- Neural Network Convolution (NNC) for Converting Ultra-Low-Dose to "Virtual" High-Dose CT Images -- Deep-Fext: Deep Feature Extraction for Vessel Segmentation and Centerline Prediction -- Product Space Decompositions for Continuous Representations of Brain Connectivity -- Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks -- Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging -- Tversky Loss Function for Image Segmentation Using 3D Fully Convolutional Deep Networks. Tipo de medio : Computadora Summary : This book constitutes the refereed proceedings of the 8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017, held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 44 full papers presented in this volume were carefully reviewed and selected from 63 submissions. The main aim of this workshop is to help advance scientific research within the broad field of machine learning in medical imaging. The workshop focuses on major trends and challenges in this area, and presents works aimed to identify new cutting-edge techniques and their use in medical imaging. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Machine Learning in Medical Imaging : 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Proceedings [documento electrónico] / Wang, Qian, ; Shi, Yinghuan, ; Suk, Heung-Il, ; Suzuki, Kenji, . - 1 ed. . - [s.l.] : Springer, 2017 . - XV, 391 p. 134 ilustraciones.
ISBN : 978-3-319-67389-9
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Visión por computador IngenierÃa de software Informática Médica Procesamiento de datos Inteligencia artificial Informática de la Salud MinerÃa de datos y descubrimiento de conocimientos Clasificación: 006.37 Resumen: Este libro constituye las actas arbitradas del 8º Taller Internacional sobre Aprendizaje Automático en Imágenes Médicas, MLMI 2017, celebrado junto con MICCAI 2017, en la ciudad de Quebec, QC, Canadá, en septiembre de 2017. Los 44 artÃculos completos presentados en este volumen fueron cuidadosamente revisado y seleccionado entre 63 presentaciones. El objetivo principal de este taller es ayudar a avanzar en la investigación cientÃfica dentro del amplio campo del aprendizaje automático en imágenes médicas. El taller se centra en las principales tendencias y desafÃos en esta área, y presenta trabajos destinados a identificar nuevas técnicas de vanguardia y su uso en imágenes médicas. Nota de contenido: From Large to Small Organ Segmentation in CT Using Regional Context -- Motion Corruption Detection in Breast DCE-MRI -- Detection and Localization of Drosophila Egg Chambers in Microscopy Images -- Growing a Random Forest with Fuzzy Spatial Features for Fully Automatic Artery-specific Coronary Calcium Scoring -- Atlas of Classifiers for Brain MRI Segmentation -- Dictionary Learning and Sparse Coding-based Denoising for High-Resolution Task Functional Connectivity MRI Analysis -- Yet Another ADNI Machine Learning Paper? Paving The Way Towards Fully-reproducible Research on Classification of Alzheimer's Disease -- Multi-Factorial Age Estimation from Skeletal and Dental MRI Volumes -- Automatic Classification of Proximal Femur Fractures Based on Attention Models -- Joint Supervoxel Classification Forest for Weakly-Supervised Organ Segmentation -- Accurate and Consistent Hippocampus Segmentation Through Convolutional LSTM and View Ensemble -- STAR: Spatio-Temporal Architecture for Super-Resolution inLow-Dose CT Perfusion -- Classification of Alzheimer's Disease by Cascaded Convolutional Neural Networks Using PET Images -- Finding Dense Supervoxel Correspondence of Cone-Beam Computed Tomography Images -- Multi-Scale Volumetric ConvNet with Nested Residual Connections for Segmentation of Anterior Cranial Base -- Feature Learning and Fusion of Multimodality Neuroimaging and Genetic Data for Multi-Status Dementia Diagnosis -- 3D Convolutional Neural Networks with Graph Refinement for Airway Segmentation Using Incomplete Data Labels -- Efficient Groupwise Registration for Brain MRI by Fast Initialization -- Sparse Multi-View Task-centralized Learning for ASD Diagnosis -- Inter-Subject Similarity Guided Brain Network Modelling for MCI Diagnosis -- Scalable and Fault Tolerant Platform for Distributed Learning on Private Medical Data -- Triple-Crossing 2.5D Convolutional Neural Network for Detecting Neuronal Arbours in 3D Microscopic Images -- Longitudinally-Consistent Parcellation of Infant Population Cortical Surfaces Based on Functional Connectivity -- Gradient Boosted Trees for Corrective Learning -- Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis -- A Point Says a Lot: An Interactive Segmentation Method for MR Prostate via One-Point Labeling -- Collage CNN for Renal Cell Carcinoma Detection from CT -- Aggregating Deep Convolutional Features for Melanoma Recognition in Dermoscopy Images -- Localizing Cardiac Structures in Fetal Heart Ultrasound Video -- Deformable Registration Through Learning of Context-Specific Metric Aggregation -- Segmentation of Craniomaxillofacial Bony Structures from MRI with a 3D Deep-learning Based Cascade Framework -- 3D U-net with Multi-Level Deep Supervision: Fully Automatic Segmentation of Proximal Femur in 3D MR Images -- Indecisive Trees for Classification and Prediction of Knee Osteoarthritis -- Whole Brain Segmentation and Labeling from CT using synthetic MR Images -- Structural Connectivity Guided SparseEffective Connectivity for MCI Identification -- Fusion of High-order and Low-order Effective Connectivity Networks for MCI Classification -- Novel Effective Connectivity Network Inference for MCI Identification -- Reconstruction of Thin-Slice Medical Images Using Generative Adversarial Network -- Neural Network Convolution (NNC) for Converting Ultra-Low-Dose to "Virtual" High-Dose CT Images -- Deep-Fext: Deep Feature Extraction for Vessel Segmentation and Centerline Prediction -- Product Space Decompositions for Continuous Representations of Brain Connectivity -- Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks -- Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging -- Tversky Loss Function for Image Segmentation Using 3D Fully Convolutional Deep Networks. Tipo de medio : Computadora Summary : This book constitutes the refereed proceedings of the 8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017, held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 44 full papers presented in this volume were carefully reviewed and selected from 63 submissions. The main aim of this workshop is to help advance scientific research within the broad field of machine learning in medical imaging. The workshop focuses on major trends and challenges in this area, and presents works aimed to identify new cutting-edge techniques and their use in medical imaging. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Social Robotics : 9th International Conference, ICSR 2017, Tsukuba, Japan, November 22-24, 2017, Proceedings Tipo de documento: documento electrónico Autores: Kheddar, Abderrahmane, ; Yoshida, Eiichi, ; Ge, Shuzhi Sam, ; Suzuki, Kenji, ; Cabibihan, John-John, ; Eyssel, Friederike, ; He, Hongsheng, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2017 Número de páginas: XV, 761 p. 307 ilustraciones ISBN/ISSN/DL: 978-3-319-70022-9 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Inteligencia artificial Computadoras Propósitos especiales Interfaces de usuario (sistemas informáticos) La interacción persona-ordenador Software de la aplicacion Sistemas de propósito especial y basados ​​en aplicaciones Interfaces de usuario e interacción persona-computadora Aplicaciones informáticas y de sistemas de información Clasificación: 006.3 Resumen: Este libro constituye las actas arbitradas de la 9.ª Conferencia Internacional sobre Robótica Social, ICSR 2016, celebrada en Tsukuba, Japón, en noviembre de 2017. Los 74 artÃculos completos revisados ​​presentados fueron cuidadosamente revisados ​​y seleccionados entre 110 presentaciones. El tema de la conferencia de 2017 es: Robots interactivos incorporados. Además de las sesiones técnicas, ICSR 2017 incluyó cuatro talleres: 1) Inteligencia de robots sociales para la interacción social humano-robot de robots de servicios; 2) Seguridad y comodidad humanas en entornos sociales interactivos entre humanos y robots; 3) Modos de Interacción para Robots Sociales (MISR 2017): Posturas, Gestos y Microinteracciones; y 4) Religión en Robótica. Nota de contenido: Learning Affordances for Assistive Robots -- Initial Design, Implementation and Technical Evaluation of a Context-aware Proxemics Planner for a Social Robot -- An Image based Non-verbal Behaviour analysis of HRI -- Do Social Rewards from Robots Enhance Offline Improvements in Motor Skills? -- How the Timing and Magnitude of Robot Errors Influence Peoples' Trust of Robots in an Emergency Scenarios -- The Iterative Development of the Humanoid Robot Kaspar: An Assistive Robot for Children with Autism -- The Interaction Between Voice and Appearance in the Embodiment of a Robot Tutor -- Shape It – The Influence of Robot Body Shape on Gender Perception in Robots -- A Telepresence Robot in Residential Care: Family Increasingly Present, Personnel Worried about Privacy -- Influence of Robot's Interaction Style on Performance in a Stroop Task -- `Autistic Robots' for Embodied Emulation of Behaviors Typically Seen in Children with Different Autism Severities -- Learning Relationships between Objects and Places by Multimodal Spatial Concept with Bag of Objects -- There once was a Robot Storyteller: Measuring the Effects of Emotion and non-verbal Behaviour -- Field testing of the influence of assistive wear on the physical fitness of nursing-care workers -- Developing Interaction Scenarios with a Humanoid Robot to Encourage Visual Perspective Taking Skills in Children with Autism –  Preliminary Proof of Concept Tests -- Human-like Hand Reaching by Motion Prediction using Long Short-Term Memory -- User's Personality and Activity Influence on HRI Comfortable Distances -- A Need for Service Robots among Health Care Professionals in Hospitals and Housing Services -- Do you think I approve of that? Designing facial expressions for a robot -- Robotic Device to Mediate Human-Human Hug-Driven Remote Communication -- RoMa: A Hi-tech Robotic Mannequin for the Fashion Industry -- Walk the talk: Gestures in  mobile interaction -- Gaze Behavioral Adaptation towards Group Members for Providing Effective Recommendations -- Subtle Reaction and Response Time Effects in Human-Robot Touch Interaction -- Young EFL learners' attitude towards RALL: an observational study focusing on motivation, anxiety, and interaction -- Design of a Cloud-Based Robotic Platform for Accompanying and Interacting with Humans -- Influence of Environmental Context on Recognition Rates -- Creating lively behaviors in social robots -- What Went Wrong and Why? Diagnosing Situated  Interaction Failures in the Wild -- Toward 3D Printed Prosthetic Hands that can Satisfy Psychosocial Needs: Grasping Force Comparisons between a Prosthetic Hand and Human Hands -- Integrating a Humanoid Robot into ECHONET-based Smart Home Environments -- A Robot that Encourages Self-Disclosure by Hug -- Hand Gestures and Verbal Acknowledgments Improve Human-Robot Rapport -- Do Audio-Visual Stimuli Change Hug Impressions? -- Impact of Tutoring Strategies in Grounded Lexicon Learning -- Yes, Of Course? An Investigation on Obedience and Feelings of Shame towards a Robot -- Dance with me! Child-robot interaction in the wild -- Rethinking the Why of Socially Assistive Robotics through Design -- Role-oriented Designing: A Methodology to Designing for Appearance and Interaction Ways of Customized Professional Social Robots -- Exploring Users' Reactions Towards Tangible Implicit Probes for Measuring Human-Robot Engagement -- Gaze-Based Hints During Child - Robot GamePlay -- Gender Difference in Expectation for Domestic Robots: A Survey in Japan -- Motor Actions Predictions and Controls for the NAO Robot when Playing Hand Clapping Games -- The importance of mutual gaze in human-robot interaction -- About Decisions During Human-Robot Shared Plan Achievement: Who Should Act and How? -- Improving User's Performance by Motivation: Matching Robot Interaction Strategy with User's Regulatory State -- Social group motion in robots -- Shopping Mall Robots – Opportunities and Constraints from the Retailer and Manager Perspective -- Dynamic Gesture Recognition for Social Robots -- Embodiment, Privacy and Social Robots: May I remember you? -- A TV Chat Robot with Time-Shifting Function for Daily-Use Communication -- Naturalistic Conversational Gaze Control for Humanoid Robots - A First Step -- Design and Implementation of a Device Management System for Healthcare Assistive Robots: Sensor Manager System Version 2 -- Dialogue Design for a Robot-Based Face-Mirroring Game to Engage Autistic Children with Emotional Expressions -- Look but Don't Stare: Mutual Gaze Interaction in Social Robots -- Recognition of Gestural Behaviors Expressed by a Humanoid Robotic Platform for Teaching Affect Recognition to Children with Autism - A Healthy Subjects Pilot Study -- A Visual Environment for Reactive Robot Programming of Macro-level Behaviors -- Hand in Hand with Robots: Differences between Experienced and Naive Users in Human-Robot Handover Scenarios -- Subjective Stress in Hybrid Collaboration -- Development of Control Mechanism for Safety Enhancement in Bilateral ControlRobot Applications -- Understanding anthropomorphism: Anthropomorphism is not a reverse process of dehumanization -- An Evaluation Tool of the Effect of Robots in Eldercare on the Sense of Safety and Security -- Becoming Real: An Anthropological Approach to Evaluating Robots in the Real World -- Human Perceptions of the Severity of Domestic Robot Errors -- What Can We Learn from the Long-Term Users of a Social Robot? -- Adaptive Emotional Chatting Behavior to Increase the Sociability of Robots -- Measuring Children's Perceptions of Robots' Social Competence: Design and Validation -- Rule Extraction Method Considering Reliability for Synchronized Behavior of Group Robots in Multi-party Conversations -- Omnidirectional Traveling Instruction for Behavior Navigation -- News Application Adaptation based on User Sensory Profile -- Robot Compliant Behaviour with Mixed-Initiative Interaction in an Obstacle Avoidance Scenario -- "Xylotism": A Tablet-Based Application to Teach Music to Children with Autism -- Starting a Conversation by Multi-Robot Cooperative Behavior -- Adaptive Strategies for Multi-Party Interactions with Robots in Public Spaces. Tipo de medio : Computadora Summary : This book constitutes the refereed proceedings of the 9th International Conference on Social Robotics, ICSR 2016, held in Tsukuba, Japan, in November 2017. The 74 revised full papers presented were carefully reviewed and selected from 110 submissions. The theme of the 2017 conference is: Embodied Interactive Robots. In addition to the technical sessions, ICSR 2017 included four workshops: 1) Social Robot Intelligence for Social Human-Robot Interaction of Service Robots; 2) Human Safety and Comfort in Human-Robot Interactive Social Environments; 3) Modes of Interaction for Social Robots (MISR 2017): Postures, Gestures and Microinteractions; and 4) Religion in Robotics. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Social Robotics : 9th International Conference, ICSR 2017, Tsukuba, Japan, November 22-24, 2017, Proceedings [documento electrónico] / Kheddar, Abderrahmane, ; Yoshida, Eiichi, ; Ge, Shuzhi Sam, ; Suzuki, Kenji, ; Cabibihan, John-John, ; Eyssel, Friederike, ; He, Hongsheng, . - 1 ed. . - [s.l.] : Springer, 2017 . - XV, 761 p. 307 ilustraciones.
ISBN : 978-3-319-70022-9
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Idioma : Inglés (eng)
Palabras clave: Inteligencia artificial Computadoras Propósitos especiales Interfaces de usuario (sistemas informáticos) La interacción persona-ordenador Software de la aplicacion Sistemas de propósito especial y basados ​​en aplicaciones Interfaces de usuario e interacción persona-computadora Aplicaciones informáticas y de sistemas de información Clasificación: 006.3 Resumen: Este libro constituye las actas arbitradas de la 9.ª Conferencia Internacional sobre Robótica Social, ICSR 2016, celebrada en Tsukuba, Japón, en noviembre de 2017. Los 74 artÃculos completos revisados ​​presentados fueron cuidadosamente revisados ​​y seleccionados entre 110 presentaciones. El tema de la conferencia de 2017 es: Robots interactivos incorporados. Además de las sesiones técnicas, ICSR 2017 incluyó cuatro talleres: 1) Inteligencia de robots sociales para la interacción social humano-robot de robots de servicios; 2) Seguridad y comodidad humanas en entornos sociales interactivos entre humanos y robots; 3) Modos de Interacción para Robots Sociales (MISR 2017): Posturas, Gestos y Microinteracciones; y 4) Religión en Robótica. Nota de contenido: Learning Affordances for Assistive Robots -- Initial Design, Implementation and Technical Evaluation of a Context-aware Proxemics Planner for a Social Robot -- An Image based Non-verbal Behaviour analysis of HRI -- Do Social Rewards from Robots Enhance Offline Improvements in Motor Skills? -- How the Timing and Magnitude of Robot Errors Influence Peoples' Trust of Robots in an Emergency Scenarios -- The Iterative Development of the Humanoid Robot Kaspar: An Assistive Robot for Children with Autism -- The Interaction Between Voice and Appearance in the Embodiment of a Robot Tutor -- Shape It – The Influence of Robot Body Shape on Gender Perception in Robots -- A Telepresence Robot in Residential Care: Family Increasingly Present, Personnel Worried about Privacy -- Influence of Robot's Interaction Style on Performance in a Stroop Task -- `Autistic Robots' for Embodied Emulation of Behaviors Typically Seen in Children with Different Autism Severities -- Learning Relationships between Objects and Places by Multimodal Spatial Concept with Bag of Objects -- There once was a Robot Storyteller: Measuring the Effects of Emotion and non-verbal Behaviour -- Field testing of the influence of assistive wear on the physical fitness of nursing-care workers -- Developing Interaction Scenarios with a Humanoid Robot to Encourage Visual Perspective Taking Skills in Children with Autism –  Preliminary Proof of Concept Tests -- Human-like Hand Reaching by Motion Prediction using Long Short-Term Memory -- User's Personality and Activity Influence on HRI Comfortable Distances -- A Need for Service Robots among Health Care Professionals in Hospitals and Housing Services -- Do you think I approve of that? Designing facial expressions for a robot -- Robotic Device to Mediate Human-Human Hug-Driven Remote Communication -- RoMa: A Hi-tech Robotic Mannequin for the Fashion Industry -- Walk the talk: Gestures in  mobile interaction -- Gaze Behavioral Adaptation towards Group Members for Providing Effective Recommendations -- Subtle Reaction and Response Time Effects in Human-Robot Touch Interaction -- Young EFL learners' attitude towards RALL: an observational study focusing on motivation, anxiety, and interaction -- Design of a Cloud-Based Robotic Platform for Accompanying and Interacting with Humans -- Influence of Environmental Context on Recognition Rates -- Creating lively behaviors in social robots -- What Went Wrong and Why? Diagnosing Situated  Interaction Failures in the Wild -- Toward 3D Printed Prosthetic Hands that can Satisfy Psychosocial Needs: Grasping Force Comparisons between a Prosthetic Hand and Human Hands -- Integrating a Humanoid Robot into ECHONET-based Smart Home Environments -- A Robot that Encourages Self-Disclosure by Hug -- Hand Gestures and Verbal Acknowledgments Improve Human-Robot Rapport -- Do Audio-Visual Stimuli Change Hug Impressions? -- Impact of Tutoring Strategies in Grounded Lexicon Learning -- Yes, Of Course? An Investigation on Obedience and Feelings of Shame towards a Robot -- Dance with me! Child-robot interaction in the wild -- Rethinking the Why of Socially Assistive Robotics through Design -- Role-oriented Designing: A Methodology to Designing for Appearance and Interaction Ways of Customized Professional Social Robots -- Exploring Users' Reactions Towards Tangible Implicit Probes for Measuring Human-Robot Engagement -- Gaze-Based Hints During Child - Robot GamePlay -- Gender Difference in Expectation for Domestic Robots: A Survey in Japan -- Motor Actions Predictions and Controls for the NAO Robot when Playing Hand Clapping Games -- The importance of mutual gaze in human-robot interaction -- About Decisions During Human-Robot Shared Plan Achievement: Who Should Act and How? -- Improving User's Performance by Motivation: Matching Robot Interaction Strategy with User's Regulatory State -- Social group motion in robots -- Shopping Mall Robots – Opportunities and Constraints from the Retailer and Manager Perspective -- Dynamic Gesture Recognition for Social Robots -- Embodiment, Privacy and Social Robots: May I remember you? -- A TV Chat Robot with Time-Shifting Function for Daily-Use Communication -- Naturalistic Conversational Gaze Control for Humanoid Robots - A First Step -- Design and Implementation of a Device Management System for Healthcare Assistive Robots: Sensor Manager System Version 2 -- Dialogue Design for a Robot-Based Face-Mirroring Game to Engage Autistic Children with Emotional Expressions -- Look but Don't Stare: Mutual Gaze Interaction in Social Robots -- Recognition of Gestural Behaviors Expressed by a Humanoid Robotic Platform for Teaching Affect Recognition to Children with Autism - A Healthy Subjects Pilot Study -- A Visual Environment for Reactive Robot Programming of Macro-level Behaviors -- Hand in Hand with Robots: Differences between Experienced and Naive Users in Human-Robot Handover Scenarios -- Subjective Stress in Hybrid Collaboration -- Development of Control Mechanism for Safety Enhancement in Bilateral ControlRobot Applications -- Understanding anthropomorphism: Anthropomorphism is not a reverse process of dehumanization -- An Evaluation Tool of the Effect of Robots in Eldercare on the Sense of Safety and Security -- Becoming Real: An Anthropological Approach to Evaluating Robots in the Real World -- Human Perceptions of the Severity of Domestic Robot Errors -- What Can We Learn from the Long-Term Users of a Social Robot? -- Adaptive Emotional Chatting Behavior to Increase the Sociability of Robots -- Measuring Children's Perceptions of Robots' Social Competence: Design and Validation -- Rule Extraction Method Considering Reliability for Synchronized Behavior of Group Robots in Multi-party Conversations -- Omnidirectional Traveling Instruction for Behavior Navigation -- News Application Adaptation based on User Sensory Profile -- Robot Compliant Behaviour with Mixed-Initiative Interaction in an Obstacle Avoidance Scenario -- "Xylotism": A Tablet-Based Application to Teach Music to Children with Autism -- Starting a Conversation by Multi-Robot Cooperative Behavior -- Adaptive Strategies for Multi-Party Interactions with Robots in Public Spaces. Tipo de medio : Computadora Summary : This book constitutes the refereed proceedings of the 9th International Conference on Social Robotics, ICSR 2016, held in Tsukuba, Japan, in November 2017. The 74 revised full papers presented were carefully reviewed and selected from 110 submissions. The theme of the 2017 conference is: Embodied Interactive Robots. In addition to the technical sessions, ICSR 2017 included four workshops: 1) Social Robot Intelligence for Social Human-Robot Interaction of Service Robots; 2) Human Safety and Comfort in Human-Robot Interactive Social Environments; 3) Modes of Interaction for Social Robots (MISR 2017): Postures, Gestures and Microinteractions; and 4) Religion in Robotics. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
