Marginal Space Learning for Medical Image Analysis (Record no. 55387)
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000 -LEADER | |
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fixed length control field | 03039nam a22005055i 4500 |
001 - CONTROL NUMBER | |
control field | 978-1-4939-0600-0 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20200421111838.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 140416s2014 xxu| s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9781493906000 |
-- | 978-1-4939-0600-0 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 006.6 |
100 1# - AUTHOR NAME | |
Author | Zheng, Yefeng. |
245 10 - TITLE STATEMENT | |
Title | Marginal Space Learning for Medical Image Analysis |
Sub Title | Efficient Detection and Segmentation of Anatomical Structures / |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | XX, 268 p. 122 illus., 58 illus. in color. |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | 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. |
520 ## - SUMMARY, ETC. | |
Summary, etc | 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. |
700 1# - AUTHOR 2 | |
Author 2 | Comaniciu, Dorin. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | http://dx.doi.org/10.1007/978-1-4939-0600-0 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks |
264 #1 - | |
-- | New York, NY : |
-- | Springer New York : |
-- | Imprint: Springer, |
-- | 2014. |
336 ## - | |
-- | text |
-- | txt |
-- | rdacontent |
337 ## - | |
-- | computer |
-- | c |
-- | rdamedia |
338 ## - | |
-- | online resource |
-- | cr |
-- | rdacarrier |
347 ## - | |
-- | text file |
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-- | rda |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computer science. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Radiology. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial intelligence. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computer graphics. |
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computer Science. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computer Imaging, Vision, Pattern Recognition and Graphics. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Imaging / Radiology. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial Intelligence (incl. Robotics). |
912 ## - | |
-- | ZDB-2-SCS |
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