Marginal Space Learning for Medical Image Analysis

Efficient Detection and Segmentation of Anatomical Structures

Yefeng Zheng, Dorin Comaniciu (Autoren)

Buch | Hardcover

268 Seiten

2014 | 2014 ed.
Springer-Verlag New York Inc.
978-1-4939-0599-7 (ISBN)

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Automatic 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.

Introduction.- Marginal Space Learning.- Comparison of Marginal Space Learning and Full Space Learning in 2D.- Constrained Marginal Space Learning.- Part-Based Object Detection and Segmentation.- Optimal Mean Shape for Nonrigid Object Detection and Segmentation.- Nonrigid Object Segmentation: Application to Four-Chamber Heart Segmentation.- Applications of Marginal Space Learning in Medical Imaging.- Conclusions and Future Work.

Zusatzinfo	58 Illustrations, color; 64 Illustrations, black and white; XX, 268 p. 122 illus., 58 illus. in color.
Verlagsort	New York
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Grafik / Design ► Digitale Bildverarbeitung
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Medizinische Fachgebiete ► Radiologie / Bildgebende Verfahren ► Radiologie
ISBN-10	1-4939-0599-6 / 1493905996
ISBN-13	978-1-4939-0599-7 / 9781493905997
Zustand	Neuware