Shape Analysis in Medical Image Analysis

ISBN-13: 9783319038124 / Angielski / Twarda / 2014 / 442 str.

Shuo Li; Joao Manuel R. S. Tavares

Opis

This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice.This volume treats topics such as for example, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms. This work will be of interest to researchers, students and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computational vision, computer sciences, human motion, mathematics, medical imaging, medicine, pattern recognition and physics.

Spis treści

Preface.- Part I: Methods and Models.- 1. Shape Analysis for Brain Structures: A Review, by Bernard Ng, Matthew Toews, Stanley Durrleman, Yonggang Shi.- 2. Shape Analysis in Molecular Imaging, by Fei Gao, Pengcheng Shi.- 3. Variational Shape Representation for Modeling, Elastic Registration and Segmentation, by Amal A. Farag, Ahmed Shalaby, Aly A. Farag.- 4. Image Computing Based on Bayesian Models, by Zhong Xue, Stephen Wong.- 5. Shape-Constrained Deformable Models and Applications in Medical Imaging, by Jürgen Weese, Irina Waechter-Stehle, Lyubomir Zagorchev, Jochen Peters.- Part II: Application Cases.- 6. Accurate Pathology Segmentation in FLAIR MRI for Robust Shape Characterization, by April Khademi, Alan R. Moody, Anastasios Venetsanopoulos.- 7. Groupwise Registration of Brain Images, by Zhenyu Tang, Yong Fan.- 8. Modeling of Lung Nodules from LDCT of the Human Chest: Algorithms and Evaluation for CAD Systems, by Amal A. Farag, James Graham, Salwa Elshazly, Mohamed Al-Mogy, Aly Farag.- 9. Analyzing the Shape and Motion of the Lung and Heart in Dynamic Pulmonary Imaging, by Jianming Liang, Tim McInerney, Demetri Terzopoulos.- 10. Epithelial Cell Segmentation via Shape Ranking, by Alberto Santamaria-Pang, Yuchi Huang, Jens Rittscher.- 11. Computational Modeling of the Spine, by T. Klinder, S. Kadoury, C. Lorenz.- 12. Shape Constraints for the Left Ventricle Segmentation from Cardiac Cine MRI Based on Snake Models, by Yuanquan Wang, Yuwei Wu, Yunde Jia.- 13. An Optical Flow Approach to Assessment of Ventricular Shape Change Based on Echocardiography, by Amir A. Amini, Nirmanmoh Bhatia, Rita Longaker, Motaz Alshaher, Marcus Stoddard and Vahid Tavakoli.

Blurb

This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification, and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice.

This volume treats topics such as, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms.

This work will be of interest to researchers, students, and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computational vision, computer sciences, human motion, mathematics, medical imaging, medicine, pattern recognition and physics.