Registration Methods for Pulmonary Image Analysis : Integration of Morphological and Physiological Knowledge

Alexander Schmidt-Richberg

ISBN 10: 3658016612 / ISBN 13: 9783658016616

Published by Springer Fachmedien Wiesbaden, 2014

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783658016616

Bibliographic Details

• Title: Registration Methods for Pulmonary Image Analysis : Integration of Morphological and Physiological Knowledge
• Publisher: Springer Fachmedien Wiesbaden
• Publication Date: 2014
• Language: English
• ISBN 10: 3658016612
• ISBN 13: 9783658016616
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 210W x 148H x 11D millimeters 210 millimeters width by 148 millimeters height by 11 millimeters depth
• Weight: 251 grams

About this title

Synopsis

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.

About 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.