Developing an effective computer-aided diagnosis (CAD) system for lung cancer is of great clinical importance and can significantly increase the patient's chance for survival. For this reason, CAD systems for lung cancer have been investigated in a large number of research studies. A typical CAD system for lung cancer diagnosis is composed of four main processing steps: segmentation of the lung fields, detection of nodules inside the lung fields, segmentation of the detected nodules, and diagnosis of the nodules as benign or malignant. This book overviews the current state-of-the-art techniques that have been developed to implement each of these CAD processing steps.

  • Overviews the latest state-of-the-art diagnostic CAD systems for lung cancer imaging and diagnosis
  • Offers detailed coverage of 3D and 4D image segmentation
  • Illustrates unique fully automated detection systems coupled with 4D Computed Tomography (CT)
  • Written by authors who are world-class researchers in the biomedical imaging sciences
  • Includes extensive references at the end of each chapter to enhance further study

Ayman El-Baz is a professor, university scholar, and chair of the Bioengineering Department at the University of Louisville, Louisville, Kentucky. He earned his bachelor’s and master’s degrees in electrical engineering in 1997 and 2001, respectively. He earned his doctoral degree in electrical engineering from the University of Louisville in 2006. In 2009, he was named a Coulter Fellow for his contributions to the field of biomedical translational research. He has 17 years of hands-on experience in the fields of bio-imaging modeling and noninvasive computer-assisted diagnosis systems. He has authored or coauthored more than 500 technical articles (132 journals, 23 books, 57 book chapters, 211 refereed-conference papers, 137 abstracts, and 27 U.S. patents and disclosures).



Jasjit S. Suri is an innovator, scientist, a visionary, an industrialist, and an internationally known world leader in biomedical engineering. He has spent over 25 years in the field of biomedical engineering/devices and its management. He received his doctorate from the University of Washington, Seattle, and his business management sciences degree from Weatherhead School of Management, Case Western Reserve University, Cleveland, Ohio. He was awarded the President’s Gold Medal in 1980 and named a Fellow of the American Institute of Medical and Biological Engineering for his outstanding contributions in 2004. In 2018, he was awarded the Marquis Life Time Achievement Award for his outstanding contributions and dedication to medical imaging and its management.

chapter 1|28 pages

Computer-Aided Diagnosis of Chronic Obstructive Pulmonary Disease Using Accurate Lung Air Volume Estimation in Computed Tomographic Imaging

ByHadi Moghadas-Dastjerdi, Mohammad Reza Ahmadzadeh, Abbas Samani

chapter 2|20 pages

Early Detection of Chronic Obstructive Pulmonary Disease: Influence on Lung Cancer Epidemiology

ByAmany F. Elbehairy, Ahmed Sadaka

chapter 3|26 pages

Dual Energy Computed Tomography for Lung Cancer Diagnosis and Characterization

ByVictor Gonzalez-Perez, Estanislao Arana, David Moratal

chapter 4|22 pages

X-Ray Dark-Field Imaging of Lung Cancer in Mice

ByDeniz A. Bölükbas, Darcy E. Wagner

chapter 5|10 pages

Lung Cancer Screening Using Low-Dose Computed Tomography

ByAlison Wenholz, Ikenna Okereke

chapter 7|34 pages

Automated Lung Cancer Detection From PET/CT Images Using Texture and Fractal Descriptors

ByK. Punithavathy, Sumathi Poobal, M. M. Ramya

chapter 9|22 pages

Lung Nodule Classification Basedon the Integration of a Higher-Order Markov-Gibbs Random Field Appearance Model and Geometric Features

ByAhmed Shaffie, Ahmed Soliman, Ali Mahmoud, Mohammed Ghazal, Hassan Hajjdiab, Robert Keynton, Guruprasad Giridharan, Adel Elmaghraby, Jasjit S. Suri, Ayman El-Baz

chapter 10|18 pages

Smoking Cessation and Lung Cancer Screening Programs: The Rationale and Method to Integration

ByMeghan Cahill, Brooke Crawford O'Neill, Kimberly Del Mauro, Courtney Yeager, Bradley B. Pua

chapter 11|32 pages

Automatic Lung Segmentation and Interobserver Variability Analysis

ByJoel C. M. Than, Norliza M. Noor, Luca Saba, Omar M. Rijal, Rosminah M. Kassim, Ashari Yunus, Chuen R. Ng, Jasjit S. Suri

chapter 12|32 pages

Classification of Diseased Lungs Using a Combination of Riesz and Gabor Transforms and Machine Learning

ByLuca Saba, Joel C. M. Than, Norliza M. Noor, Omar M. Rijal, Rosminah M. Kassim, Ashari Yunus, Harman S. Suri, Michele Porcu, Jasjit S. Suri

chapter 13|22 pages

An Unsupervised Parametric MixtureModel for Automatic Three-DimensionalLung Segmentation

ByMohammed Ghazal, Samr Ali, Mohanad AlKhodari, Ayman El-Baz

chapter 14|20 pages

How Deep Learning Is Changing the Landscape of Lung Cancer Diagnosis

BySarfaraz Hussein, Ulas Bagci

chapter 15|22 pages

Early Assessment of Radiation-Induced Lung Injury

ByAhmed Soliman, Fahmi Khalifa, Ahmed Shaffie, Ali Mahmoud, Neal Dunlap, Brian Wang, Adel Elmaghraby, Georgy Gimel'farb, Robert Keynton, Mohammed Ghazal, Jasjit S. Suri, Ayman El-Baz