Overview

Lung cancer is one of the most common cancers in men and women worldwide. Early diagnosis of lung cancer can significantly increase the chances of a patient’s survival, yet early detection has historically been difficult. As a result, there has been a great deal of progress in the development of accurate and fast diagnostic tools in recent years. Lung Cancer and Imaging provides an introduction to the methods currently used in lung cancer diagnosis and the promising new techniques that are emerging. Areas covered include the major trends and challenges in lung cancer detection and diagnosis, classification of cancer types, lung feature extraction in joint PET/CT images, and algorithms in the area of low dosage CT lung cancer images.

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9780750325387

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Ayman El-Baz is a professor, university scholar, and the chair of the Bioengineering Department at the University of Louisville, Kentucky. El-Baz has 17 years of hands-on experience in the fields of bioimaging modeling and non-invasive computer-assisted diagnosis systems. In 2009, he was named a Coulter Fellow for his contributions to the field of biomedical translational research. He has authored or co-authored more than 500 technical articles across journals, books, book chapters, conference papers, abstracts, and US patents and disclosures. Jasjit S Suri is an innovator, scientist, industrialist and an internationally known world leader in biomedical engineering. He has spent more than 25 years in the field of biomedical engineering/devices. In 2018, he was awarded the Marquis Lifetime Achievement Award for his outstanding contributions and dedication to medical imaging and its management.

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