Detection Systems in Lung Cancer and Imaging, Volume 1
Language: English
Published by IOP Publishing Ltd Jan 2022, 2022
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Condition: New
US$ 300.60
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Add to basketItem description from seller
Neuware - This book focuses on major trends and challenges in the detection of lung cancer, presenting work aimed at identifying new techniques and their use in biomedical analysis. This volume covers recent advancements in lung cancer and imaging detection and classification, examining the main applications of Computer aided diagnosis (CAD) relating to lung cancer: lung nodule segmentation, lung nodule classification, and Big Data in lung cancer. Ideal for academics working in lung cancer, data-mining, machine learning, deep learning and reinforcement learning, as well as industry professionals working in the areas of healthcare, lung cancer imaging, machine learning, deep learning and reinforcement learning, this edited collection comprises an essential reference for researchers at the forefront of the field, and provides a high-level entry point for more advanced students. Key Features: - Unique focus on advance work in detection system and classification systems. - An updated reference for lung cancer detection via imaging. - Focus on progressive deep learning and machine learning applications for more effective detection.…
Seller Inventory # 9780750333535
- Title
- Detection Systems in Lung Cancer and Imaging, Volume 1
- Author
- Ayman El-Baz
- Publisher
- IOP Publishing Ltd Jan 2022
- Publication year
- 2022
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 0750333537
- ISBN 13
- 9780750333535
- Item weight
- 640 grams
- Dimensions
- 254x178x14 mm
This book focuses on major trends and challenges in the detection of lung cancer, presenting work aimed at identifying new techniques and their use in biomedical analysis. This volume covers recent advancements in lung cancer and imaging detection and classification, examining the main applications of Computer aided diagnosis (CAD) relating to lung cancer: lung nodule segmentation, lung nodule classification, and Big Data in lung cancer. Ideal for academics working in lung cancer, data-mining, machine learning, deep learning and reinforcement learning, as well as industry professionals working in the areas of healthcare, lung cancer imaging, machine learning, deep learning and reinforcement learning, this edited collection comprises an essential reference for researchers at the forefront of the field, and provides a high-level entry point for more advanced students.
Key Features:
- Unique focus on advance work in detection system and classification systems.
- An updated reference for lung cancer detection via imaging.
- Focus on progressive deep learning and machine learning applications for more effective
detection.
"Synopsis" may belong to another edition of this title.
About the Author
Jasjit S. Suri, PhD, MBA is a Fellow of IEEE, AIMBE, SVM, AIUM, and APVS. He is currently the Chairman of AtheroPoint, Roseville, CA, USA, dedicated to imaging technologies for cardiovascular and stroke. He has nearly 22,000 citations, co-authored 50 books, and has an H-index of 72.
"About the title" may belong to another edition of this title.
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