Información del autor
Autor Melbourne, Andrew |
Documentos disponibles escritos por este autor (5)
Crear una solicitud de compra Refinar búsquedaData Driven Treatment Response Assessment and Preterm, Perinatal, and Paediatric Image Analysis / Melbourne, Andrew ; Licandro, Roxane ; DiFranco, Matthew ; Rota, Paolo ; Gau, Melanie ; Kampel, Martin ; Aughwane, Rosalind ; Moeskops, Pim ; Schwartz, Ernst ; Robinson, Emma ; Makropoulos, Antonios
TÃtulo : Data Driven Treatment Response Assessment and Preterm, Perinatal, and Paediatric Image Analysis : First International Workshop, DATRA 2018 and Third International Workshop, PIPPI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings Tipo de documento: documento electrónico Autores: Melbourne, Andrew, ; Licandro, Roxane, ; DiFranco, Matthew, ; Rota, Paolo, ; Gau, Melanie, ; Kampel, Martin, ; Aughwane, Rosalind, ; Moeskops, Pim, ; Schwartz, Ernst, ; Robinson, Emma, ; Makropoulos, Antonios, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2018 Número de páginas: XI, 180 p. 74 ilustraciones ISBN/ISSN/DL: 978-3-030-00807-9 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 Visión por computador Informática Médica Unidades aritméticas y lógicas informáticas. Informática de la Salud Estructuras aritméticas y lógicas Clasificación: 006.3 Resumen: Este libro constituye las actas conjuntas arbitradas del Primer Taller Internacional sobre Evaluación de Respuesta al Tratamiento Basada en Datos, DATRA 2018 y el Tercer Taller Internacional sobre Análisis de Imágenes Prematuros, Perinatales y Pediátricas, PIPPI 2018, celebrado en conjunto con la 21a Conferencia Internacional sobre Imágenes Médicas y Intervención Asistida por Computadora, MICCAI 2018, en Granada, España, en septiembre de 2018. Los 5 artÃculos completos presentados en DATRA 2018 y los 12 artÃculos completos presentados en PIPPI 2018 fueron cuidadosamente revisados ​​y seleccionados. Los artÃculos de DATRA cubren una amplia gama de tecnologÃas de reconocimiento de patrones para abordar problemas clÃnicos relacionados con el análisis de seguimiento de datos médicos con enfoque en el análisis de la progresión de la malignidad, modelos de respuesta al tratamiento asistidos por computadora y detección de anomalÃas en la retroalimentación de recuperación. Los artÃculos de PIPPI cubren temas de enfoques avanzados de análisis de imágenes centrados en el análisis del crecimiento y desarrollo en el perÃodo fetal, infantil y pediátrico. Nota de contenido: DeepCS: Deep Convolutional Neural Network and SVM based Single Image Super-Resolution -- Automatic Segmentation of Thigh Muscle in Longitudinal 3D T1-Weighted Magnetic Resonance (MR) Images -- Detecting Bone Lesions in Multiple Myeloma Patient Using Transfer Learning -- Quantification of Local Metabolic Tumor Volume Changes by Registering Blended PET-CT Images for Prediction of Pathologic Tumor Response -- Optimizing External Surface Sensor Locations for Respiratory Tumor Motion Prediction -- Segmentation of Fetal Adipose Tissue Using Efficient CNNs for Portable Ultrasound -- Automatic Shadow Detection in 2D Ultrasound Images -- Multi-Channel Groupwise Registration to Construct and Ultrasound-Specific Fetal Brain Atlas -- Investigating Brain Age Deviation in Preterm Infants: A Deep Learning Approach -- Segmentation of Pelvic Vessels in Pediatric MRI Using a Patch-Based Deep Learning Approach -- Multi-View Image Reconstruction: Application to Fetal Ultrasound Compounding -- EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging Without External Trackers -- Better Feature Matching for Placental Panorama Construction -- Combining Deep Learning and Multi-Atlas Label Fusion for Automated Placenta Segmentation from 3DUS -- LSTM Spatial Co-transformer Networks for Registration of 3D Fetal US and MR Brain Images -- Automatic and Efficient Standard Plane Recognition in Fetal Ultrasound Images via Multi-Scale Dense Networks -- Paediatric Liver Segmentation for Low-Contrast CT Images. Tipo de medio : Computadora Summary : This book constitutes the refereed joint proceedings of the First International Workshop on Data Driven Treatment Response Assessment, DATRA 2018 and the Third International Workshop on Preterm, Perinatal and Paediatric Image Analysis, PIPPI 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 5 full papers presented at DATRA 2018 and the 12 full papers presented at PIPPI 2018 were carefully reviewed and selected. The DATRA papers cover a wide range of exploring pattern recognition technologies for tackling clinical issues related to the follow-up analysis of medical data with focus on malignancy progression analysis, computer-aided models of treatment response, and anomaly detection in recovery feedback. The PIPPI papers cover topics of advanced image analysis approaches focused on the analysis of growth and development in the fetal, infantand paediatric period. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Data Driven Treatment Response Assessment and Preterm, Perinatal, and Paediatric Image Analysis : First International Workshop, DATRA 2018 and Third International Workshop, PIPPI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings [documento electrónico] / Melbourne, Andrew, ; Licandro, Roxane, ; DiFranco, Matthew, ; Rota, Paolo, ; Gau, Melanie, ; Kampel, Martin, ; Aughwane, Rosalind, ; Moeskops, Pim, ; Schwartz, Ernst, ; Robinson, Emma, ; Makropoulos, Antonios, . - 1 ed. . - [s.l.] : Springer, 2018 . - XI, 180 p. 74 ilustraciones.
ISBN : 978-3-030-00807-9
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: Inteligencia artificial Visión por computador Informática Médica Unidades aritméticas y lógicas informáticas. Informática de la Salud Estructuras aritméticas y lógicas Clasificación: 006.3 Resumen: Este libro constituye las actas conjuntas arbitradas del Primer Taller Internacional sobre Evaluación de Respuesta al Tratamiento Basada en Datos, DATRA 2018 y el Tercer Taller Internacional sobre Análisis de Imágenes Prematuros, Perinatales y Pediátricas, PIPPI 2018, celebrado en conjunto con la 21a Conferencia Internacional sobre Imágenes Médicas y Intervención Asistida por Computadora, MICCAI 2018, en Granada, España, en septiembre de 2018. Los 5 artÃculos completos presentados en DATRA 2018 y los 12 artÃculos completos presentados en PIPPI 2018 fueron cuidadosamente revisados ​​y seleccionados. Los artÃculos de DATRA cubren una amplia gama de tecnologÃas de reconocimiento de patrones para abordar problemas clÃnicos relacionados con el análisis de seguimiento de datos médicos con enfoque en el análisis de la progresión de la malignidad, modelos de respuesta al tratamiento asistidos por computadora y detección de anomalÃas en la retroalimentación de recuperación. Los artÃculos de PIPPI cubren temas de enfoques avanzados de análisis de imágenes centrados en el análisis del crecimiento y desarrollo en el perÃodo fetal, infantil y pediátrico. Nota de contenido: DeepCS: Deep Convolutional Neural Network and SVM based Single Image Super-Resolution -- Automatic Segmentation of Thigh Muscle in Longitudinal 3D T1-Weighted Magnetic Resonance (MR) Images -- Detecting Bone Lesions in Multiple Myeloma Patient Using Transfer Learning -- Quantification of Local Metabolic Tumor Volume Changes by Registering Blended PET-CT Images for Prediction of Pathologic Tumor Response -- Optimizing External Surface Sensor Locations for Respiratory Tumor Motion Prediction -- Segmentation of Fetal Adipose Tissue Using Efficient CNNs for Portable Ultrasound -- Automatic Shadow Detection in 2D Ultrasound Images -- Multi-Channel Groupwise Registration to Construct and Ultrasound-Specific Fetal Brain Atlas -- Investigating Brain Age Deviation in Preterm Infants: A Deep Learning Approach -- Segmentation of Pelvic Vessels in Pediatric MRI Using a Patch-Based Deep Learning Approach -- Multi-View Image Reconstruction: Application to Fetal Ultrasound Compounding -- EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging Without External Trackers -- Better Feature Matching for Placental Panorama Construction -- Combining Deep Learning and Multi-Atlas Label Fusion for Automated Placenta Segmentation from 3DUS -- LSTM Spatial Co-transformer Networks for Registration of 3D Fetal US and MR Brain Images -- Automatic and Efficient Standard Plane Recognition in Fetal Ultrasound Images via Multi-Scale Dense Networks -- Paediatric Liver Segmentation for Low-Contrast CT Images. Tipo de medio : Computadora Summary : This book constitutes the refereed joint proceedings of the First International Workshop on Data Driven Treatment Response Assessment, DATRA 2018 and the Third International Workshop on Preterm, Perinatal and Paediatric Image Analysis, PIPPI 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 5 full papers presented at DATRA 2018 and the 12 full papers presented at PIPPI 2018 were carefully reviewed and selected. The DATRA papers cover a wide range of exploring pattern recognition technologies for tackling clinical issues related to the follow-up analysis of medical data with focus on malignancy progression analysis, computer-aided models of treatment response, and anomaly detection in recovery feedback. The PIPPI papers cover topics of advanced image analysis approaches focused on the analysis of growth and development in the fetal, infantand paediatric period. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Fetal, Infant and Ophthalmic Medical Image Analysis : International Workshop, FIFI 2017, and 4th International Workshop, OMIA 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, Proceedings Tipo de documento: documento electrónico Autores: Cardoso, M. Jorge, ; Arbel, Tal, ; Melbourne, Andrew, ; Bogunovic, Hrvoje, ; Moeskops, Pim, ; Chen, Xinjian, ; Schwartz, Ernst, ; Garvin, Mona, ; Robinson, Emma, ; Trucco, Emanuele, ; Ebner, Michael, ; Xu, Yanwu, ; Makropoulos, Antonios, ; Desjardin, Adrien, ; Vercauteren, Tom, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2017 Número de páginas: XIII, 252 p. 109 ilustraciones ISBN/ISSN/DL: 978-3-319-67561-9 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 Inteligencia artificial Informática Médica Procesamiento de datos Ciencias de la Computación Informática Estadistica matematica Informática de la Salud MinerÃa de datos y descubrimiento de conocimientos Modelos de Computación Probabilidad y EstadÃstica en Informática Clasificación: 006.37 Resumen: Este libro constituye las actas conjuntas arbitradas del Taller internacional sobre análisis de imágenes fetales e infantiles, FIFI 2017, y el 6.º Taller internacional sobre análisis de imágenes médicas oftálmicas, OMIA 2017, celebrado junto con la 20.ª Conferencia internacional sobre imágenes médicas y análisis de imágenes asistidas por computadora. Intervención, MICCAI 2017, en la ciudad de Québec, QC, Canadá, en septiembre de 2017. Los 8 artÃculos completos presentados en FIFI 2017 y los 20 artÃculos completos presentados en OMIA 2017 fueron cuidadosamente revisados ​​y seleccionados. Los artÃculos de FIFI presentan investigaciones sobre enfoques avanzados de análisis de imágenes centrados en el análisis del crecimiento y desarrollo en el perÃodo fetal, infantil y pediátrico. Los artÃculos de OMIA cubren diversos temas en el campo del análisis de imágenes oftálmicas. Tipo de medio : Computadora Summary : This book constitutes the refereed joint proceedings of the International Workshop on Fetal and Infant Image Analysis, FIFI 2017, and the 6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 8 full papers presented at FIFI 2017 and the 20 full papers presented at OMIA 2017 were carefully reviewed and selected. The FIFI papers feature research on advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period. The OMIA papers cover various topics in the field of ophthalmic image analysis. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Fetal, Infant and Ophthalmic Medical Image Analysis : International Workshop, FIFI 2017, and 4th International Workshop, OMIA 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, Proceedings [documento electrónico] / Cardoso, M. Jorge, ; Arbel, Tal, ; Melbourne, Andrew, ; Bogunovic, Hrvoje, ; Moeskops, Pim, ; Chen, Xinjian, ; Schwartz, Ernst, ; Garvin, Mona, ; Robinson, Emma, ; Trucco, Emanuele, ; Ebner, Michael, ; Xu, Yanwu, ; Makropoulos, Antonios, ; Desjardin, Adrien, ; Vercauteren, Tom, . - 1 ed. . - [s.l.] : Springer, 2017 . - XIII, 252 p. 109 ilustraciones.
ISBN : 978-3-319-67561-9
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 Inteligencia artificial Informática Médica Procesamiento de datos Ciencias de la Computación Informática Estadistica matematica Informática de la Salud MinerÃa de datos y descubrimiento de conocimientos Modelos de Computación Probabilidad y EstadÃstica en Informática Clasificación: 006.37 Resumen: Este libro constituye las actas conjuntas arbitradas del Taller internacional sobre análisis de imágenes fetales e infantiles, FIFI 2017, y el 6.º Taller internacional sobre análisis de imágenes médicas oftálmicas, OMIA 2017, celebrado junto con la 20.ª Conferencia internacional sobre imágenes médicas y análisis de imágenes asistidas por computadora. Intervención, MICCAI 2017, en la ciudad de Québec, QC, Canadá, en septiembre de 2017. Los 8 artÃculos completos presentados en FIFI 2017 y los 20 artÃculos completos presentados en OMIA 2017 fueron cuidadosamente revisados ​​y seleccionados. Los artÃculos de FIFI presentan investigaciones sobre enfoques avanzados de análisis de imágenes centrados en el análisis del crecimiento y desarrollo en el perÃodo fetal, infantil y pediátrico. Los artÃculos de OMIA cubren diversos temas en el campo del análisis de imágenes oftálmicas. Tipo de medio : Computadora Summary : This book constitutes the refereed joint proceedings of the International Workshop on Fetal and Infant Image Analysis, FIFI 2017, and the 6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 8 full papers presented at FIFI 2017 and the 20 full papers presented at OMIA 2017 were carefully reviewed and selected. The FIFI papers feature research on advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period. The OMIA papers cover various topics in the field of ophthalmic image analysis. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis : First International Workshop, ASMUS 2020, and 5th International Workshop, PIPPI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4-8, 2020, Proceedings Tipo de documento: documento electrónico Autores: Hu, Yipeng, ; Licandro, Roxane, ; Noble, J. Alison, ; Hutter, Jana, ; Aylward, Stephen, ; Melbourne, Andrew, ; Abaci Turk, Esra, ; Torrents Barrena, Jordina, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2020 Número de páginas: XIV, 345 p. 188 ilustraciones, 116 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-60334-2 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: Procesamiento de imágenes Visión por computador Ciencias sociales Red de computadoras Software de la aplicacion Imágenes por computadora visión reconocimiento de patrones y gráficos Aplicación informática en ciencias sociales y del comportamiento. Computadoras y Educación Redes de comunicación informática Aplicaciones informáticas y de sistemas de información Clasificación: 6 Resumen: Este libro constituye las actas del Primer Taller Internacional sobre Avances en la Simplificación del UltraSound Médico, ASMUS 2020, y el 5to Taller Internacional sobre Análisis de Imágenes Perinatales, Prematuros y Pediátricas, PIPPI 2020, celebrado junto con MICCAI 2020, la 23a Conferencia Internacional sobre Medicina. Computación de la Imagen e Intervención Asistida por Computadora. La conferencia estaba prevista para realizarse en Lima, Perú, pero cambió a un evento en lÃnea debido a la pandemia de coronavirus. Para ASMUS 2020, se aceptaron 19 contribuciones de 26 presentaciones; Las 14 contribuciones del taller de PIPPI fueron cuidadosamente revisadas y seleccionadas entre 21 presentaciones. Los artÃculos se organizaron en secciones temáticas denominadas: diagnóstico y medición; segmentación, subtÃtulos y mejora; localización y orientación; robótica y evaluación de habilidades, y PIPPI 2020. Nota de contenido: Remote Intelligent Assisted Diagnosis System for Hepatic Echinococcosis -- Calibrated Bayesian neural networks to estimate gestational age and its uncertainty on fetal brain ultrasound images -- Automatic Optic Nerve Sheath Measurement in Point-of-Care Ultrasound -- Deep Learning for Automatic Spleen Length Measurement in Sickle Cell Disease Patients -- Cross-Device Cross-Anatomy Adaptation Network for Ultrasound Video Analysis -- Guidewire Segmentation in 4D Ultrasound Sequences Using Recurrent Fully Convolutional Networks -- Embedding Weighted Feature Aggregation Network with Domain Knowledge Integration for Breast Ultrasound Image Segmentation -- A Curriculum Learning Based Approach to Captioning Ultrasound Images -- Deep Image Translation for Enhancing Simulated Ultrasound Images -- Localizing 2D Ultrasound Probe from Ultrasound Image Sequences Using Deep Learning for Volume Reconstruction -- Augmented Reality-Based Lung Ultrasound Scanning Guidance -- Multimodality Biomedical Image Registration using Free Point Transformer Networks -- Label Efficient Localization of Fetal Brain Biometry Planes In Ultrasound Through Metric Learning -- Automatic C-plane detection in pelvic oor transperineal volumetric ultrasound -- Unsupervised Cross-domain Image Classification by Distance Metric Guided Feature Alignment -- Dual-Robotic Ultrasound System for In Vivo Prostate Tomography -- IoT-based Remote Control Study of a Robotic Trans-esophageal Ultrasound Probe via LAN and 5G -- Differentiating Operator Skill during Routine Fetal Ultrasound Scanning using Probe Motion Tracking -- Kinematics Data Representations for Skills Assessment in Ultrasound-Guided Needle Insertion -- 3D Fetal Pose Estimation with Adaptive Variance and Conditional Generative Adversarial Network -- Atlas-based segmentation of the human embryo using deep learning with minimal supervision -- Deformable Slice-to-Volume Registration for Reconstruction of Quantitative T2* Placental and Fetal MRI -- A Smartphone-based System for Real-time Early Childhood Caries Diagnosis -- Automated Detection of Congenital Heart Disease in Fetal Ultrasound Screening -- Harmonised segmentation of neonatal brain MRI: a domain adaptation approach -- A multi-task approach using positional information for ultrasound placenta segmentation -- Spontaneous preterm birth prediction using convolutional neural networks -- Multi-Modal Perceptual Adversarial Learning for Longitudinal Prediction of Infant MR Images -- Efficient multi-class fetal brain segmentation in high resolution MRI reconstructions with noisy labels -- Deep Learning Spatial Compounding from Multiple Fetal Head Ultrasound Acquisitions -- Brain volume and neuropsychological differences in extremely preterm adolescents -- Automatic Detection of Neonatal Brain Injury on MRI -- Unbiased atlas construction for neonatal cortical surfaces via unsupervised learning. Tipo de medio : Computadora Summary : This book constitutes the proceedings of the First International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2020, and the 5th International Workshop on Perinatal, Preterm and Paediatric Image Analysis, PIPPI 2020, held in conjunction with MICCAI 2020, the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention. The conference was planned to take place in Lima, Peru, but changed to an online event due to the Coronavirus pandemic. For ASMUS 2020, 19 contributions were accepted from 26 submissions; the 14 contributions from the PIPPI workshop were carefully reviewed and selected from 21 submissions. The papers were organized in topical sections named: diagnosis and measurement; segmentation, captioning and enhancement; localisation and guidance; robotics and skill assessment, and PIPPI 2020. . Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis : First International Workshop, ASMUS 2020, and 5th International Workshop, PIPPI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4-8, 2020, Proceedings [documento electrónico] / Hu, Yipeng, ; Licandro, Roxane, ; Noble, J. Alison, ; Hutter, Jana, ; Aylward, Stephen, ; Melbourne, Andrew, ; Abaci Turk, Esra, ; Torrents Barrena, Jordina, . - 1 ed. . - [s.l.] : Springer, 2020 . - XIV, 345 p. 188 ilustraciones, 116 ilustraciones en color.
ISBN : 978-3-030-60334-2
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: Procesamiento de imágenes Visión por computador Ciencias sociales Red de computadoras Software de la aplicacion Imágenes por computadora visión reconocimiento de patrones y gráficos Aplicación informática en ciencias sociales y del comportamiento. Computadoras y Educación Redes de comunicación informática Aplicaciones informáticas y de sistemas de información Clasificación: 6 Resumen: Este libro constituye las actas del Primer Taller Internacional sobre Avances en la Simplificación del UltraSound Médico, ASMUS 2020, y el 5to Taller Internacional sobre Análisis de Imágenes Perinatales, Prematuros y Pediátricas, PIPPI 2020, celebrado junto con MICCAI 2020, la 23a Conferencia Internacional sobre Medicina. Computación de la Imagen e Intervención Asistida por Computadora. La conferencia estaba prevista para realizarse en Lima, Perú, pero cambió a un evento en lÃnea debido a la pandemia de coronavirus. Para ASMUS 2020, se aceptaron 19 contribuciones de 26 presentaciones; Las 14 contribuciones del taller de PIPPI fueron cuidadosamente revisadas y seleccionadas entre 21 presentaciones. Los artÃculos se organizaron en secciones temáticas denominadas: diagnóstico y medición; segmentación, subtÃtulos y mejora; localización y orientación; robótica y evaluación de habilidades, y PIPPI 2020. Nota de contenido: Remote Intelligent Assisted Diagnosis System for Hepatic Echinococcosis -- Calibrated Bayesian neural networks to estimate gestational age and its uncertainty on fetal brain ultrasound images -- Automatic Optic Nerve Sheath Measurement in Point-of-Care Ultrasound -- Deep Learning for Automatic Spleen Length Measurement in Sickle Cell Disease Patients -- Cross-Device Cross-Anatomy Adaptation Network for Ultrasound Video Analysis -- Guidewire Segmentation in 4D Ultrasound Sequences Using Recurrent Fully Convolutional Networks -- Embedding Weighted Feature Aggregation Network with Domain Knowledge Integration for Breast Ultrasound Image Segmentation -- A Curriculum Learning Based Approach to Captioning Ultrasound Images -- Deep Image Translation for Enhancing Simulated Ultrasound Images -- Localizing 2D Ultrasound Probe from Ultrasound Image Sequences Using Deep Learning for Volume Reconstruction -- Augmented Reality-Based Lung Ultrasound Scanning Guidance -- Multimodality Biomedical Image Registration using Free Point Transformer Networks -- Label Efficient Localization of Fetal Brain Biometry Planes In Ultrasound Through Metric Learning -- Automatic C-plane detection in pelvic oor transperineal volumetric ultrasound -- Unsupervised Cross-domain Image Classification by Distance Metric Guided Feature Alignment -- Dual-Robotic Ultrasound System for In Vivo Prostate Tomography -- IoT-based Remote Control Study of a Robotic Trans-esophageal Ultrasound Probe via LAN and 5G -- Differentiating Operator Skill during Routine Fetal Ultrasound Scanning using Probe Motion Tracking -- Kinematics Data Representations for Skills Assessment in Ultrasound-Guided Needle Insertion -- 3D Fetal Pose Estimation with Adaptive Variance and Conditional Generative Adversarial Network -- Atlas-based segmentation of the human embryo using deep learning with minimal supervision -- Deformable Slice-to-Volume Registration for Reconstruction of Quantitative T2* Placental and Fetal MRI -- A Smartphone-based System for Real-time Early Childhood Caries Diagnosis -- Automated Detection of Congenital Heart Disease in Fetal Ultrasound Screening -- Harmonised segmentation of neonatal brain MRI: a domain adaptation approach -- A multi-task approach using positional information for ultrasound placenta segmentation -- Spontaneous preterm birth prediction using convolutional neural networks -- Multi-Modal Perceptual Adversarial Learning for Longitudinal Prediction of Infant MR Images -- Efficient multi-class fetal brain segmentation in high resolution MRI reconstructions with noisy labels -- Deep Learning Spatial Compounding from Multiple Fetal Head Ultrasound Acquisitions -- Brain volume and neuropsychological differences in extremely preterm adolescents -- Automatic Detection of Neonatal Brain Injury on MRI -- Unbiased atlas construction for neonatal cortical surfaces via unsupervised learning. Tipo de medio : Computadora Summary : This book constitutes the proceedings of the First International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2020, and the 5th International Workshop on Perinatal, Preterm and Paediatric Image Analysis, PIPPI 2020, held in conjunction with MICCAI 2020, the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention. The conference was planned to take place in Lima, Peru, but changed to an online event due to the Coronavirus pandemic. For ASMUS 2020, 19 contributions were accepted from 26 submissions; the 14 contributions from the PIPPI workshop were carefully reviewed and selected from 21 submissions. The papers were organized in topical sections named: diagnosis and measurement; segmentation, captioning and enhancement; localisation and guidance; robotics and skill assessment, and PIPPI 2020. . Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Smart Ultrasound Imaging and Perinatal, Preterm and Paediatric Image Analysis : First International Workshop, SUSI 2019, and 4th International Workshop, PIPPI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings Tipo de documento: documento electrónico Autores: Wang, Qian, ; Gomez, Alberto, ; Hutter, Jana, ; McLeod, Kristin, ; Zimmer, Veronika, ; Zettinig, Oliver, ; Licandro, Roxane, ; Robinson, Emma, ; Christiaens, Daan, ; Turk, Esra Abaci, ; Melbourne, Andrew, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2019 Número de páginas: XVII, 190 p. 97 ilustraciones, 68 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-32875-7 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 Procesamiento de imágenes Visión por computador Software de la aplicacion IngenierÃa Informática Red de computadoras Imágenes por computadora visión reconocimiento de patrones y gráficos Aplicaciones informáticas y de sistemas de información IngenierÃa Informática y Redes Clasificación: 006.3 Resumen: Este libro constituye las actas conjuntas arbitradas del Primer Taller Internacional sobre Imágenes por Ultrasonido Inteligentes, SUSI 2019, y el 4.º Taller Internacional sobre Análisis de Imágenes Prematuros, Perinatales y Pediátricas, PIPPI 2019, celebrado junto con la 22.ª Conferencia Internacional sobre Imágenes Médicas y Computación. -Intervención Asistida, MICCAI 2019, en Shenzhen, China, en octubre de 2019. Los 10 artÃculos completos presentados en SUSI 2019 y los 10 artÃculos completos presentados en PIPPI 2019 fueron cuidadosamente revisados ​​y seleccionados. Los artÃculos de SUSI cubren una amplia gama de aplicaciones médicas del ultrasonido en modo B, incluidas las cardÃacas (ecocardiografÃa), abdominales (hÃgado), fetales, musculoesqueléticas y pulmonares. Los artÃculos de PIPPI cubren el estudio cientÃfico detallado del crecimiento volumétrico, la mielinización y la microestructura cortical, la estructura y función de la placenta. Nota de contenido: First Workshop on Smart UltraSound Imaging -- Straight to the point: reinforcement learning for user guidance in ultrasound -- Registration of Untracked 2D Laparoscopic Ultrasound Liver Images to CT using Content-based Retrieval and Kinematic Priors -- Direct Detection and Measurement of Nuchal Translucency with Neural Networks from Ultrasound Images -- Automated left ventricle dimension measurement in 2D cardiac ultrasound via an anatomically meaningful CNN approach -- SPRNet: Automatic Fetal Standard Plane Recognition Network for Ultrasound Images -- Representation Disentanglement for Multi-task Learning with application to Fetal Ultrasound -- Adversarial Learning for Deformable Image Registration: Application to 3D Ultrasound Image Fusion -- Monitoring Achilles tendon healing progress in ultrasound imaging with convolutional neural networks -- Deep Learning-based Pneumothorax Detection in Ultrasound Videos -- Deep Learning Based Minimum Variance Beamforming for Ultrasound Imaging -- 4th Workshop on Perinatal, Preterm and Paediatric Image Analysis -- Estimation of preterm birth markers with U-Net segmentation network -- Investigating Image Registration Impact on Preterm Birth Classification: An Interpretable Deep Learning Approach -- Dual Network Generative Adversarial Networks for Pediatric Echocardiography Segmentation -- Reproducibility of Functional Connectivity Estimates in Motion Corrected Fetal fMRI -- Plug-and-Play Priors for Reconstruction-based Placental Image Registration -- A Longitudinal Study of the Evolution of the Central Sulcus' Shape in Preterm Infants using Manifold Learning -- Prediction of failure of induction of labor (IOL) from ultrasound images using radioman features -- Longitudinal analysis of fetal MRI in patients with prenatal spina bifida repair -- Quantifying Residual Motion Artifacts in Fetal fMRI Data -- Topology-preserving augmentation for CNN-based segmentation of congenital heart defects from 3D paediatric CMR. Tipo de medio : Computadora Summary : This book constitutes the refereed joint proceedings of the First International Workshop on Smart Ultrasound Imaging, SUSI 2019, and the 4th International Workshop on Preterm, Perinatal and Paediatric Image Analysis, PIPPI 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 10 full papers presented at SUSI 2019 and the 10 full papers presented at PIPPI 2019 were carefully reviewed and selected. The SUSI papers cover a wide range of medical applications of B-Mode ultrasound, including cardiac (echocardiography), abdominal (liver), fetal, musculoskeletal, and lung. The PIPPI papers cover the detailed scientific study of volumetric growth, myelination and cortical microstructure, placental structure and function. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Smart Ultrasound Imaging and Perinatal, Preterm and Paediatric Image Analysis : First International Workshop, SUSI 2019, and 4th International Workshop, PIPPI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings [documento electrónico] / Wang, Qian, ; Gomez, Alberto, ; Hutter, Jana, ; McLeod, Kristin, ; Zimmer, Veronika, ; Zettinig, Oliver, ; Licandro, Roxane, ; Robinson, Emma, ; Christiaens, Daan, ; Turk, Esra Abaci, ; Melbourne, Andrew, . - 1 ed. . - [s.l.] : Springer, 2019 . - XVII, 190 p. 97 ilustraciones, 68 ilustraciones en color.
ISBN : 978-3-030-32875-7
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 Procesamiento de imágenes Visión por computador Software de la aplicacion IngenierÃa Informática Red de computadoras Imágenes por computadora visión reconocimiento de patrones y gráficos Aplicaciones informáticas y de sistemas de información IngenierÃa Informática y Redes Clasificación: 006.3 Resumen: Este libro constituye las actas conjuntas arbitradas del Primer Taller Internacional sobre Imágenes por Ultrasonido Inteligentes, SUSI 2019, y el 4.º Taller Internacional sobre Análisis de Imágenes Prematuros, Perinatales y Pediátricas, PIPPI 2019, celebrado junto con la 22.ª Conferencia Internacional sobre Imágenes Médicas y Computación. -Intervención Asistida, MICCAI 2019, en Shenzhen, China, en octubre de 2019. Los 10 artÃculos completos presentados en SUSI 2019 y los 10 artÃculos completos presentados en PIPPI 2019 fueron cuidadosamente revisados ​​y seleccionados. Los artÃculos de SUSI cubren una amplia gama de aplicaciones médicas del ultrasonido en modo B, incluidas las cardÃacas (ecocardiografÃa), abdominales (hÃgado), fetales, musculoesqueléticas y pulmonares. Los artÃculos de PIPPI cubren el estudio cientÃfico detallado del crecimiento volumétrico, la mielinización y la microestructura cortical, la estructura y función de la placenta. Nota de contenido: First Workshop on Smart UltraSound Imaging -- Straight to the point: reinforcement learning for user guidance in ultrasound -- Registration of Untracked 2D Laparoscopic Ultrasound Liver Images to CT using Content-based Retrieval and Kinematic Priors -- Direct Detection and Measurement of Nuchal Translucency with Neural Networks from Ultrasound Images -- Automated left ventricle dimension measurement in 2D cardiac ultrasound via an anatomically meaningful CNN approach -- SPRNet: Automatic Fetal Standard Plane Recognition Network for Ultrasound Images -- Representation Disentanglement for Multi-task Learning with application to Fetal Ultrasound -- Adversarial Learning for Deformable Image Registration: Application to 3D Ultrasound Image Fusion -- Monitoring Achilles tendon healing progress in ultrasound imaging with convolutional neural networks -- Deep Learning-based Pneumothorax Detection in Ultrasound Videos -- Deep Learning Based Minimum Variance Beamforming for Ultrasound Imaging -- 4th Workshop on Perinatal, Preterm and Paediatric Image Analysis -- Estimation of preterm birth markers with U-Net segmentation network -- Investigating Image Registration Impact on Preterm Birth Classification: An Interpretable Deep Learning Approach -- Dual Network Generative Adversarial Networks for Pediatric Echocardiography Segmentation -- Reproducibility of Functional Connectivity Estimates in Motion Corrected Fetal fMRI -- Plug-and-Play Priors for Reconstruction-based Placental Image Registration -- A Longitudinal Study of the Evolution of the Central Sulcus' Shape in Preterm Infants using Manifold Learning -- Prediction of failure of induction of labor (IOL) from ultrasound images using radioman features -- Longitudinal analysis of fetal MRI in patients with prenatal spina bifida repair -- Quantifying Residual Motion Artifacts in Fetal fMRI Data -- Topology-preserving augmentation for CNN-based segmentation of congenital heart defects from 3D paediatric CMR. Tipo de medio : Computadora Summary : This book constitutes the refereed joint proceedings of the First International Workshop on Smart Ultrasound Imaging, SUSI 2019, and the 4th International Workshop on Preterm, Perinatal and Paediatric Image Analysis, PIPPI 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 10 full papers presented at SUSI 2019 and the 10 full papers presented at PIPPI 2019 were carefully reviewed and selected. The SUSI papers cover a wide range of medical applications of B-Mode ultrasound, including cardiac (echocardiography), abdominal (liver), fetal, musculoskeletal, and lung. The PIPPI papers cover the detailed scientific study of volumetric growth, myelination and cortical microstructure, placental structure and function. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis : 3rd International Workshop, UNSURE 2021, and 6th International Workshop, PIPPI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings Tipo de documento: documento electrónico Autores: Sudre, Carole H., ; Licandro, Roxane, ; Baumgartner, Christian, ; Melbourne, Andrew, ; Dalca, Adrian, ; Hutter, Jana, ; Tanno, Ryutaro, ; Abaci Turk, Esra, ; Van Leemput, Koen, ; Torrents Barrena, Jordina, ; Wells, William M., ; Macgowan, Christopher, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2021 Número de páginas: XIII, 296 p. 112 ilustraciones, 103 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-87735-4 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 Visión por computador Bioinformática Sistemas de reconocimiento de patrones BiologÃa Computacional y de Sistemas Reconocimiento de patrones automatizado Clasificación: 006.3 Resumen: Este libro constituye las actas arbitradas del Tercer Taller Internacional sobre Incertidumbre para la Utilización Segura del Aprendizaje Automático en Imágenes Médicas, UNSURE 2021, y el 6to Taller Internacional sobre Análisis de Imágenes Prematuros, Perinatales y Pediátricas, PIPPI 2021, celebrado junto con MICCAI 2021. Estaba previsto que la conferencia se celebrara en Estrasburgo, Francia, pero se celebró virtualmente debido a la pandemia de COVID-19. Para UNSURE 2021, se aceptó para publicación 13 artÃculos de 18 presentaciones. Se centran en desarrollar conciencia y fomentar la investigación en el campo del modelado de incertidumbre para permitir la implementación segura de herramientas de aprendizaje automático en el mundo clÃnico. PIPPI 2021 aceptó 14 artÃculos de las 18 presentaciones recibidas. El taller tiene como objetivo reunir métodos y experiencias de investigadores y autores que trabajan en estas cohortes más jóvenes y proporciona un foro para la discusión abierta sobre enfoques avanzados de análisis de imágenes centrados en el análisis del crecimiento y desarrollo en el perÃodo fetal, infantil y pediátrico. Nota de contenido: UNSURE 2021 - Uncertainty estimation and modelling and annotation uncertainty -- Model uncertainty estimation for medical Imaging based diagnosis -- Accurate simulation of operating system updates in neuroimaging using Monte-Carlo arithmetic -- Leveraging uncertainty estimates to improve segmentation performance in cardiac MR -- Improving the reliability of semantic segmentation of medical images by uncertainty modelling with Bayesian deep networks and curriculum learning -- Unpaired MR image homogeneisation by disentangled representations and its uncertainty -- Uncertainty-aware deep learning based deformable registration -- Monte Carlo Concrete DropPath for Epistemic Uncertainty Estimation in Brain Tumour segmentation -- Improving Aleatoric Uncertainty quantification in multi-annotated medical image segmentation with normalizing flows -- UNSURE 2021 – Domain shift robustness and risk management in clinical pipelines -- Task-agnostic out-of-distribution detection using kernel density estimation -- Out of distribution detection for medical images -- Robust selective classification of skin lesions with asymmetric costs -- Confidence-based Out-of-Distribution detection: a comparative study and analysis -- Novel disease detection using ensembles with regularized disagreement -- PIPPI2021 -- Automatic Placenta Abnormality Detection using Convolutional Neural Networks on Ultrasound Texture -- Simulated Half-Fourier Acquisitions Single-shot Turbo Spin Echo (HASTE) of the Fetal Brain: Application to Super-Resolution Reconstruction -- Spatio-temporal atlas of normal fetal craniofacial feature development and CNN-based ocular biometry for motion-corrected fetal MRI -- Myelination of preterm brain networks at adolescence -- A bootstrap self-training method for sequence transfer: State-of-the-art placenta segmentation in fetal MRI -- Segmentation of the cortical plate in fetal brain MRI with a topological loss -- Fetal brain MRI measurements using a deep learning landmark network with reliability estimation -- CAS-Net: Conditional Atlas Generation and Brain Segmentation for Fetal MRI -- Detection of Injury and Automated Triage of Preterm Neonatal MRI using Patch-Based Gaussian Processes -- Assessment of Regional Cortical Development through Fissure Based Gestational Age Estimation in 3D Fetal Ultrasound -- Texture-based Analysis of Fetal Organs in Fetal Growth Restriction -- Distributionally Robust Segmentation of Abnormal Fetal Brain 3D MRI -- Analysis of the Anatomical Variability of Fetal Brains with Corpus Callosum Agenesis -- Predicting preterm birth using multimodal fetal imaging. Tipo de medio : Computadora Summary : This book constitutes the refereed proceedings of the Third International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2021, and the 6th International Workshop on Preterm, Perinatal and Paediatric Image Analysis, PIPPI 2021, held in conjunction with MICCAI 2021. The conference was planned to take place in Strasbourg, France, but was held virtually due to the COVID-19 pandemic.For UNSURE 2021, 13 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. PIPPI 2021 accepted 14 papers from the 18 submissions received. The workshop aims to bring together methods and experience from researchers and authors working on these younger cohorts and provides a forum for the open discussion of advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis : 3rd International Workshop, UNSURE 2021, and 6th International Workshop, PIPPI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings [documento electrónico] / Sudre, Carole H., ; Licandro, Roxane, ; Baumgartner, Christian, ; Melbourne, Andrew, ; Dalca, Adrian, ; Hutter, Jana, ; Tanno, Ryutaro, ; Abaci Turk, Esra, ; Van Leemput, Koen, ; Torrents Barrena, Jordina, ; Wells, William M., ; Macgowan, Christopher, . - 1 ed. . - [s.l.] : Springer, 2021 . - XIII, 296 p. 112 ilustraciones, 103 ilustraciones en color.
ISBN : 978-3-030-87735-4
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 Visión por computador Bioinformática Sistemas de reconocimiento de patrones BiologÃa Computacional y de Sistemas Reconocimiento de patrones automatizado Clasificación: 006.3 Resumen: Este libro constituye las actas arbitradas del Tercer Taller Internacional sobre Incertidumbre para la Utilización Segura del Aprendizaje Automático en Imágenes Médicas, UNSURE 2021, y el 6to Taller Internacional sobre Análisis de Imágenes Prematuros, Perinatales y Pediátricas, PIPPI 2021, celebrado junto con MICCAI 2021. Estaba previsto que la conferencia se celebrara en Estrasburgo, Francia, pero se celebró virtualmente debido a la pandemia de COVID-19. Para UNSURE 2021, se aceptó para publicación 13 artÃculos de 18 presentaciones. Se centran en desarrollar conciencia y fomentar la investigación en el campo del modelado de incertidumbre para permitir la implementación segura de herramientas de aprendizaje automático en el mundo clÃnico. PIPPI 2021 aceptó 14 artÃculos de las 18 presentaciones recibidas. El taller tiene como objetivo reunir métodos y experiencias de investigadores y autores que trabajan en estas cohortes más jóvenes y proporciona un foro para la discusión abierta sobre enfoques avanzados de análisis de imágenes centrados en el análisis del crecimiento y desarrollo en el perÃodo fetal, infantil y pediátrico. Nota de contenido: UNSURE 2021 - Uncertainty estimation and modelling and annotation uncertainty -- Model uncertainty estimation for medical Imaging based diagnosis -- Accurate simulation of operating system updates in neuroimaging using Monte-Carlo arithmetic -- Leveraging uncertainty estimates to improve segmentation performance in cardiac MR -- Improving the reliability of semantic segmentation of medical images by uncertainty modelling with Bayesian deep networks and curriculum learning -- Unpaired MR image homogeneisation by disentangled representations and its uncertainty -- Uncertainty-aware deep learning based deformable registration -- Monte Carlo Concrete DropPath for Epistemic Uncertainty Estimation in Brain Tumour segmentation -- Improving Aleatoric Uncertainty quantification in multi-annotated medical image segmentation with normalizing flows -- UNSURE 2021 – Domain shift robustness and risk management in clinical pipelines -- Task-agnostic out-of-distribution detection using kernel density estimation -- Out of distribution detection for medical images -- Robust selective classification of skin lesions with asymmetric costs -- Confidence-based Out-of-Distribution detection: a comparative study and analysis -- Novel disease detection using ensembles with regularized disagreement -- PIPPI2021 -- Automatic Placenta Abnormality Detection using Convolutional Neural Networks on Ultrasound Texture -- Simulated Half-Fourier Acquisitions Single-shot Turbo Spin Echo (HASTE) of the Fetal Brain: Application to Super-Resolution Reconstruction -- Spatio-temporal atlas of normal fetal craniofacial feature development and CNN-based ocular biometry for motion-corrected fetal MRI -- Myelination of preterm brain networks at adolescence -- A bootstrap self-training method for sequence transfer: State-of-the-art placenta segmentation in fetal MRI -- Segmentation of the cortical plate in fetal brain MRI with a topological loss -- Fetal brain MRI measurements using a deep learning landmark network with reliability estimation -- CAS-Net: Conditional Atlas Generation and Brain Segmentation for Fetal MRI -- Detection of Injury and Automated Triage of Preterm Neonatal MRI using Patch-Based Gaussian Processes -- Assessment of Regional Cortical Development through Fissure Based Gestational Age Estimation in 3D Fetal Ultrasound -- Texture-based Analysis of Fetal Organs in Fetal Growth Restriction -- Distributionally Robust Segmentation of Abnormal Fetal Brain 3D MRI -- Analysis of the Anatomical Variability of Fetal Brains with Corpus Callosum Agenesis -- Predicting preterm birth using multimodal fetal imaging. Tipo de medio : Computadora Summary : This book constitutes the refereed proceedings of the Third International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2021, and the 6th International Workshop on Preterm, Perinatal and Paediatric Image Analysis, PIPPI 2021, held in conjunction with MICCAI 2021. The conference was planned to take place in Strasbourg, France, but was held virtually due to the COVID-19 pandemic.For UNSURE 2021, 13 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. PIPPI 2021 accepted 14 papers from the 18 submissions received. The workshop aims to bring together methods and experience from researchers and authors working on these younger cohorts and provides a forum for the open discussion of advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
