| Other author/creator | Cardoso, M. Jorge. |
| Other author/creator | Arbel, Tal. |
| Other author/creator | OMIA (Workshop) (4th : 2017 : Québec, Québec) |
| Other author/creator | International Conference on Medical Image Computing and Computer-Assisted Intervention (20th : 2017 : Québec, Québec) |
| Variant title |
FIFI 2017 |
| Variant title |
OMIA 2017 |
| Series |
Lecture notes in computer science, 0302-9743 ; 10554
Lecture notes in computer science ; 10554.
|
| Contents |
International Workshop on Fetal and Infant Image Analysis, FIFI 2017: Template-Free Estimation of Intracranial Volume: A Preterm Birth Animal Model Study -- Assessing Reorganisation of Functional Connectivity in the Infant Brain -- Fetal Skull Segmentation in 3D Ultrasound via Structured Geodesic Random Forest -- Fast Registration of 3D Fetal Ultrasound Images Using Learned Corresponding Salient Points -- Automatic Segmentation of the Intracranial Volume in Fetal MR Images -- Abdomen Segmentation in 3D Fetal Ultrasound Using CNN-powered Deformable Models -- Multi-organ Detection in 3D Fetal Ultrasound with Machine Learning -- Robust Regression of Brain Maturation from 3D Fetal Neurosonography Using CRNs. |
| Contents |
4th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2017: Segmentation of Retinal Blood Vessels Using Dictionary Learning Techniques -- Detecting Early Choroidal Changes Using Piecewise Rigid Image Registration and Eye-Shape Adherent Regularization -- Patch-Based Deep Convolutional Neural Network for Corneal Ulcer Area Segmentation -- Model-Driven 3-D Regularisation for Robust Segmentation of the Refractive Corneal Surfaces in Spiral OCT Scans -- Automatic Retinal Layer Segmentation Based on Live Wire for Central Serous Retinopathy -- Retinal Image Quality Classification Using Fine-Tuned CNN -- Optic Disc Detection via Deep Learning in Fundus Images -- 3D Choroid Neovascularization Growth Prediction with Combined Hyperelastic Biomechanical Model and Reaction-Diffusion Model -- Retinal Biomarker Discovery for Dementia in an Elderly Diabetic Population -- Non-rigid Registration of Retinal OCT Images Using Conditional Correlation Ratio -- Joint Optic Disc and Cup Segmentation Using Fully Convolutional and Adversarial Networks -- Automated Segmentation of the Choroid in EDI-OCT Images with Retinal Pathology Using Convolution Neural Networks -- Spatiotemporal Analysis of Structural Changes of the Lamina Cribrosa -- Fast Blur Detection and Parametric Deconvolution of Retinal Fundus Images -- Towards Topological Correct Segmentation of Macular OCT from Cascaded FCNs -- Boosted Exudate Segmentation in Retinal Images Using Residual Nets -- Development of Clinically Based Corneal Nerves Tortuosity Indexes -- A Comparative Study Towards the Establishment of an Automatic Retinal Vessel Width Measurement Technique -- Automatic Detection of Folds and Wrinkles Due to Swelling of the Optic Disc -- Representation Learning for Retinal Vasculature Embeddings. |
| Abstract |
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. -- Publisher. |
| Bibliography note | Includes bibliographical references and index. |
| Access restriction | Available only to authorized users. |
| Other forms | Also issued online. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2017952887 |
| ISBN | 9783319675602 (alk. paper) |
| ISBN | 3319675605 (alk. paper) |
| ISBN | 9783319675619 (ebook) |
| ISBN | 3319675613 (ebook) |
