Marginal Space Learning for Medical Image Analysis : Efficient Detection and Segmentation of Anatomical Structures
2014 ed.
Book Details
Format
Hardback or Cased Book
ISBN-10
1493905996
ISBN-13
9781493905997
Edition
2014 ed.
Publisher
Springer-Verlag New York Inc.
Imprint
Springer-Verlag New York Inc.
Country of Manufacture
US
Country of Publication
GB
Publication Date
Apr 17th, 2014
Print length
268 Pages
Weight
576 grams
Dimensions
24.30 x 15.80 x 2.10 cms
Product Classification:
Medical imagingMedical imagingComputer vision
Ksh 8,100.00
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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.
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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