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OverviewAutomatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications. This book presents an efficient object detection and segmentation framework, called Marginal Space Learning, which runs at a sub-second speed on a current desktop computer, faster than the state-of-the-art. Trained with a sufficient number of data sets, Marginal Space Learning is also robust under imaging artifacts, noise and anatomical variations. The book showcases 35 clinical applications of Marginal Space Learning and its extensions to detecting and segmenting various anatomical structures, such as the heart, liver, lymph nodes and prostate in major medical imaging modalities (CT, MRI, X-Ray and Ultrasound), demonstrating its efficiency and robustness. Full Product DetailsAuthor: Yefeng Zheng , Dorin ComaniciuPublisher: Springer-Verlag New York Inc. Imprint: Springer-Verlag New York Inc. Edition: Softcover reprint of the original 1st ed. 2014 Dimensions: Width: 15.50cm , Height: 1.50cm , Length: 23.50cm Weight: 4.394kg ISBN: 9781493955756ISBN 10: 1493955756 Pages: 268 Publication Date: 03 September 2016 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand We will order this item for you from a manufactured on demand supplier. Table of ContentsReviewsThis book presents a generic learning-based method for efficient 3D object detection called marginal space learning (MSL). ... Each chapter ends with a remarkable bibliography on the topics covered. This book is suited for students and researchers with interest in medical image analysis. (Oscar Bustos, zbMATH 1362.92004, 2017) “This book presents a generic learning-based method for efficient 3D object detection called marginal space learning (MSL). … Each chapter ends with a remarkable bibliography on the topics covered. This book is suited for students and researchers with interest in medical image analysis.” (Oscar Bustos, zbMATH 1362.92004, 2017) Author InformationTab Content 6Author Website:Countries AvailableAll regions |