Registration Methods for Pulmonary Image Analysis [[electronic resource] ] : Integration of Morphological and Physiological Knowledge / / by Alexander Schmidt-Richberg

• Autore: Schmidt-Richberg Alexander
• Pubblicazione: Wiesbaden : , : Springer Fachmedien Wiesbaden : , : Imprint : Springer Vieweg, , 2014
• Edizione: 1st ed. 2014.
• Descrizione fisica: 1 online resource (179 p.)
• Disciplina: 616.24075722
• Soggetto topico: Computer science; Health informatics; Computer Science, general; Health Informatics
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: ""Preface by the Series Editor""; ""Foreword""; ""Acknowledgments""; ""Abstract""; ""Contents""; ""1 Introduction""; ""1.1 Registration in pulmonary image analysis""; ""1.2 Objectives""; ""1.3 Structure of this thesis""; ""1.4 Publications""; ""2 Current methods for lung registration""; ""2.1 Intensity-based registration techniques""; ""2.1.1 Transformation models""; ""2.1.2 Regularization approaches""; ""2.1.3 Distance measures""; ""2.1.4 Algorithmic solutions""; ""2.2 Open-source implementations""; ""2.3 Discussion""; ""3 Variational image registration"" ; ""3.1 Image registration as a minimization problem""""3.1.1 The Euler-Lagrange equation""; ""3.1.2 Discretization and stability considerations""; ""3.1.3 Multi-scale registration""; ""3.2 Distance Measures""; ""3.2.1 (Normalized) Sum of Squared Differences""; ""3.2.2 Other distance measures""; ""3.3 Regularizer""; ""3.3.1 Diffusion regularization""; ""3.3.1.1 Stability properties of the explicit scheme""; ""3.3.1.2 Diffusion regularization with Fast Explicit Diffusion""; ""3.3.1.3 Additive Operator Splitting for semi-implicit solution""; ""3.3.2 Elastic regularization"" ; ""3.3.2.1 Stability properties of the explicit scheme""""3.3.2.2 Semi-implicit solution in the frequency domain""; ""3.3.3 Gaussian smoothing""; ""3.3.4 Other regularization approaches""; ""3.4 Diffeomorphic registration""; ""3.4.1 Symmetrization of forces""; ""3.5 Experiments""; ""3.5.1 Comparison of force domains""; ""3.5.2 Comparison of regularizers""; ""3.5.3 Comparison of solution schemes""; ""3.5.4 Comparison of standard and diffeomorphic registration""; ""3.6 Discussion""; ""4 Variational level set segmentation""; ""4.1 Region-based level set segmentation"" ; ""4.1.1 Internal and external energy terms""""4.1.2 Numerical solution""; ""4.1.3 Implementation""; ""4.1.4 Experiments""; ""4.2 Extended energy terms for problem-specific modeling""; ""4.2.1 Prior shape information for segmentation refinement""; ""4.2.2 Edge attraction terms""; ""4.2.3 Experiments""; ""4.3 Level sets with multiple objects""; ""4.3.1 Experiments""; ""4.4 Discussion""; ""5 Lung registration with explicit interlobular fissure alignment""; ""5.1 Combining registration and segmentation""; ""5.1.1 Current methods for integrated registration and segmentation"" ; ""5.1.2 A variational model for integrated registration and segmentation""""5.1.3 Numerical solution""; ""5.1.4 Experiments""; ""5.2 Pulmonary lobe segmentation using level sets""; ""5.2.1 Current methods for lung and lobe segmentation""; ""5.2.2 Extension of the region-based level set framework for lobe segmentation""; ""5.2.2.1 Fissure-attraction term for lobe segmentation""; ""5.2.3 Experiments""; ""5.3 Integrated registration with pulmonary lobe segmentation""; ""5.3.1 Experiments""; ""5.4 Discussion""; ""6 Sliding motion in image registration""; ""6.1 Masked Registration"" ; ""6.2 Direction-Dependent Regularization""
• Sommario/riassunto: Various applications in the field of pulmonary image analysis require a registration of CT images of the lung. For example, a registration-based estimation of the breathing motion is employed to increase the accuracy of dose distribution in radiotherapy. Alexander Schmidt-Richberg develops methods to explicitly model morphological and physiological knowledge about respiration in algorithms for the registration of thoracic CT images. The author focusses on two lung-specific issues: on the one hand, the alignment of the interlobular fissures and on the other hand, the estimation of sliding motion at the lung boundaries. He shows that by explicitly considering these aspects based on a segmentation of the respective structure, registration accuracy can be significantly improved. Contents · Registration · Segmentation · Level Set Segmentation · Motion Estimation · Sliding Motion · Integrated Registration and Segmentation Target Groups · Researchers and students of medical informatics, medical imaging · Radiologists, physicians The Author Alexander Schmidt-Richberg works as a research scientist with a focus on image registration and segmentation. He received his PhD at the Institute of Medical Informatics, University of Lübeck, Germany, in 2013. Currently, he is a member of the Biomedical Image Analysis Group, Imperial College London, UK. Editors The series Aktuelle Forschung Medizintechnik is edited by Thorsten Buzug.
• Titolo autorizzato: Registration Methods for Pulmonary Image Analysis
• ISBN: 3-658-01662-0
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910300330303321
• Lo trovi qui: Univ. Federico II
• Serie: Aktuelle Forschung Medizintechnik – Latest Research in Medical Engineering, . 2625-9354