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Books > Medicine > Other branches of medicine > Medical imaging
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Marginal Space Learning for Medical Image Analysis - Efficient Detection and Segmentation of Anatomical Structures (Hardcover, 2014 ed.)
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Marginal Space Learning for Medical Image Analysis - Efficient Detection and Segmentation of Anatomical Structures (Hardcover, 2014 ed.)
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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.
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