Guide to Medical Image Analysis [E-Book] : Methods and Algorithms / by Klaus D. Toennies.
Toennies, Klaus D., (author)
2nd ed. 2017.
London : Springer, 2017
XXIV, 589 p. 384 illus., 197 illus. in color. online resource.
Advances in Computer Vision and Pattern Recognition
Full Text
LEADER 03697nam a22004335i 4500
001 978-1-4471-7320-5
003 Springer
008 170329s2017 xxk| s |||| 0|eng d
020 |a 9781447173205 
024 7 |a 10.1007/978-1-4471-7320-5  |2 doi 
035 |a (Sirsi) a682645 
041 |a eng 
082 0 4 |a 006.37  |2 23 
082 0 4 |a 006.6  |2 23 
084 0 |a HCR - Imaging techniques in medicine 
100 1 |a Toennies, Klaus D.,  |e author 
245 1 0 |a Guide to Medical Image Analysis  |h [E-Book] :  |b Methods and Algorithms /  |c by Klaus D. Toennies. 
250 |a 2nd ed. 2017. 
264 1 |a London :  |b Springer,  |c 2017  |e (Springer LINK)  |f SpringerComputerScience20180619 
300 |a XXIV, 589 p. 384 illus., 197 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 |a Advances in Computer Vision and Pattern Recognition 
500 |a englisch 
505 0 |a The Analysis of Medical Images -- Digital Image Acquisition -- Image Storage and Transfer -- Image Enhancement -- Feature Detection -- Segmentation: Principles and Basic Techniques -- Segmentation in Feature Space -- Segmentation as a Graph Problem -- Active Contours and Active Surfaces -- Registration and Normalization -- Shape, Appearance and Spatial Relationships -- Classification and Clustering -- Validation -- Appendix. 
520 |a This comprehensive guide provides a uniquely practical, application-focused introduction to medical image analysis. The text presents a concise examination of each of the key concepts, enabling the reader to understand the interdependencies between them before delving deeper into the derivations and technical details. This fully updated new edition has been enhanced with material on the latest developments in the field, whilst retaining the original focus on segmentation, classification and registration. Topics and features: Presents learning objectives, exercises and concluding remarks in each chapter, in addition to a glossary of abbreviations Describes a range of common imaging techniques, reconstruction techniques and image artifacts, and discusses the archival and transfer of images Reviews an expanded selection of techniques for image enhancement, feature detection, feature generation, segmentation, registration, and validation (NEW) Examines analysis methods in view of image-based guidance in the operating room, designed to aid the operator in adapting their intervention during an operation (NEW) Discusses the use of deep convolutional networks for segmentation and labeling tasks, describing how this network architecture differs from multi-layer perceptrons (NEW) Includes appendices on Markov random field optimization, variational calculus and principal component analysis This clearly-written guide/reference serves as a classroom-tested textbook for courses on medical image processing and analysis, with suggestions for course outlines supplied in the preface. Professionals in medical imaging technology, as well as computer scientists and electrical engineers specializing in medical applications, will also find the book an ideal resource for self-study. 
596 |a 1 
650 0 |a Computer science. 
650 0 |a Image processing. 
650 0 |a Radiology. 
650 4 |a image analysis 
650 4 |a image processing 
650 4 |a medical imaging 
856 4 0 |u  |z Volltext 
915 |a zzwFZJ3 
932 |a Computer Science (Springer-11645) 
949 |a XX(682645.1)  |w AUTO  |c 1  |i 682645-1001  |l ELECTRONIC  |m ZB  |r N  |s Y  |t E-BOOK  |u 19/6/2018  |x ZB-D  |z UNKNOWN  |0 NEL  |1 ONLINE