ISBN: 9780750333573 - detection systems in lung cancer and imaging (2): volume 2 (iop ebooks, band 2) (8 Ergebnisse)

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Hardback. Zustand: New.

Zustand: New. In English.

Hardback. Zustand: New.

Zustand: New.

Hardcover. Zustand: new. Hardcover. This book covers recent advancements in lung cancer and imaging, covering detection and classification. This volume examines Lung Nodule Detection, Lung Nodule and Features Extraction, and Modern Approaches for Lung Nodule Diagnosis. Nodule detection focuses on algorithmic and deep learning practises, and their related CT imaging and dynamic programming methods. The classification applications of texture and shape analysis for nodules are covered, including computerised methods for more effective detection. Finally, the book examines the modern approaches used for nodule diagnosis. Specific focus is placed on deep learning for automated classification, machine learning for data analysis, and CT automatic detection of nodules.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. This book covers recent advancements in lung cancer and imaging, covering detection and classification. This volume examines Lung Nodule Detection, Lung Nodule and Features Extraction, and Modern Approaches for Lung Nodule Diagnosis. An essential read for academics working in lung cancer, data-mining, machine learning, deep learning and reinforcement learning. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Buch. Zustand: Neu. Neuware - This book covers recent advancements in lung cancer and imaging, covering detection and classification. This volume examines Lung Nodule Detection, Lung Nodule and Features Extraction, and Modern Approaches for Lung Nodule Diagnosis. Nodule detection focuses on algorithmic and deep learning practises, and their related CT imaging and dynamic programming methods. The classification applications of texture and shape analysis for nodules are covered, including computerised methods for more effective detection. Finally, the book examines the modern approaches used for nodule diagnosis. Specific focus is placed on deep learning for automated classification, machine learning for data analysis, and CT automatic detection of nodules.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.…