Table Of ContentLung Imaging and CADx
Lung Imaging and CADx
Edited by
Ayman El-Baz and Jasjit S. Suri
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Library of Congress Cataloging-in-Publication Data
Names: El-Baz, Ayman S., editor. | Suri, Jasjit S., editor.
Title: Lung imaging and CADx / [edited by] Ayman El-Baz and Jasjit Suri.
Description: Boca Raton : Taylor & Francis, 2018.
Identifiers: LCCN 2018054774 | ISBN 9781138050914 (hardback : alk. paper)
Subjects: | MESH: Lung Neoplasms—diagnostic imaging | Image Interpretation,
Computer-Assisted
Classification: LCC RC280.L8 | NLM WF 658 | DDC 616.99/424075—dc23
LC record available at https://lccn.loc.gov/2018054774
Visit the Taylor & Francis Web site at
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With love and affection to my mother and father,
whose loving spirit sustains me still
Ayman El-Baz
To my late loving parents, my wife, and loving children
Jasjit S. Suri
Table of Contents
Acknowledgments ix
Preface xi
Contributors xiii
Editors xix
1. Computer-Aided Diagnosis of Chronic Obstructive Pulmonary Disease Using
Accurate Lung Air Volume Estimation in Computed Tomographic Imaging 1
Hadi Moghadas-Dastjerdi, Mohammad Reza Ahmadzadeh, and Abbas Samani
2. Early Detection of Chronic Obstructive Pulmonary Disease: Influence on Lung
Cancer Epidemiology 29
Amany F. Elbehairy and Ahmed Sadaka
3. Dual Energy Computed Tomography for Lung Cancer Diagnosis
and Characterization 49
Victor Gonzalez-Perez, Estanislao Arana, and David Moratal
4. X-Ray Dark-Field Imaging of Lung Cancer in Mice 75
Deniz A. Bölükbas and Darcy E. Wagner
5. Lung Cancer Screening Using Low-Dose Computed Tomography 97
Alison Wenholz and Ikenna Okereke
6. Computer-Aided Diagnosis of Lung Nodules: Systems for Estimation of Lung
Cancer Probability and False-Positive Reduction of Lung Nodule Detection 107
Mizuho Nishio
7. Automated Lung Cancer Detection From PET/CT Images Using Texture
and Fractal Descriptors 133
K. Punithavathy, Sumathi Poobal, and M. M. Ramya
8. Lung Cancer Risk of a Population Exposed to Airborne Particles:
The Contribution of Different Activities and Microenvironments 167
L. Stabile and G. Buonanno
9. Lung Nodule Classification Based on the Integration of a Higher-Order
Markov-Gibbs Random Field Appearance Model and Geometric Features 203
Ahmed Shaffie, Ahmed Soliman, Ali Mahmoud, Mohammed Ghazal,
Hassan Hajjdiab, Robert Keynton, Guruprasad Giridharan, Adel Elmaghraby,
Jasjit S. Suri, and Ayman El-Baz
vii
viii Table of Contents
10. Smoking Cessation and Lung Cancer Screening Programs: The Rationale
and Method to Integration 225
Meghan Cahill, Brooke Crawford O’Neill, Kimberly Del Mauro,
Courtney Yeager, and Bradley B. Pua
11. Automatic Lung Segmentation and Interobserver Variability Analysis 243
Joel C. M. Than, Norliza M. Noor, Luca Saba, Omar M. Rijal,
Rosminah M. Kassim, Ashari Yunus, Chuen R. Ng, and Jasjit S. Suri
12. Classification of Diseased Lungs Using a Combination of Riesz and Gabor
Transforms and Machine Learning 275
Luca Saba, Joel C. M. Than, Norliza M. Noor, Omar M. Rijal,
Rosminah M. Kassim, Ashari Yunus, Harman S. Suri, Michele Porcu,
and Jasjit S. Suri
13. An Unsupervised Parametric Mixture Model for Automatic Three-Dimensional
Lung Segmentation 307
Mohammed Ghazal, Samr Ali, Mohanad AlKhodari, and Ayman El-Baz
14. How Deep Learning Is Changing the Landscape of Lung Cancer Diagnosis 329
Sarfaraz Hussein and Ulas Bagci
15. Early Assessment of Radiation-Induced Lung Injury 349
Ahmed Soliman, Fahmi Khalifa, Ahmed Shaffie, Ali Mahmoud, Neal Dunlap,
Brian Wang, Adel Elmaghraby, Georgy Gimel’farb, Robert Keynton,
Mohammed Ghazal, Jasjit S. Suri, and Ayman El-Baz
Index 371
Acknowledgments
The completion of this book could not have been possible without the participation
and assistance of so many people whose names may not all be enumerated. Their
contributions are sincerely appreciated and gratefully acknowledged. However, the
editors would like to express their deep appreciation and indebtedness particularly to
Dr. Ali H. Mahmoud and Ahmed Shaffie for their endless support.
Ayman El-Baz
Jasjit S. Suri
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