Medical image recognition, segmentation and parsing : machine learning and multiple object approaches

This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of-the-art approaches based on machine learning, for recognizing or detecting, parsing or...

Full description

Saved in:
Bibliographic Details
Other Authors: Zhou, S. Kevin, (Editor)
Format: eBook
Language: English
Published: Amsterdam : Elsevier, [2016]
Series: Elsevier and MICCAI Society book series.
Subjects:
ISBN: 9780128026762
0128026766
9780128025819
0128025816
Physical Description: 1 online resource : illustrations

Cover

Table of contents

LEADER 05890cam a2200493 i 4500
001 kn-ocn932289263
003 OCoLC
005 20240717213016.0
006 m o d
007 cr cn|||||||||
008 151216s2016 ne a ob 001 0 eng d
040 |a N$T  |b eng  |e rda  |e pn  |c N$T  |d IDEBK  |d N$T  |d YDXCP  |d OCLCF  |d CDX  |d UIU  |d EBLCP  |d NLE  |d KNOVL  |d OTZ  |d COO  |d UAB  |d B24X7  |d OCLCQ  |d K6U  |d D6H  |d U3W  |d OCLCQ  |d AU@  |d WYU  |d OCLCA  |d MERER  |d OCLCO  |d OCLCA  |d OCLCQ  |d OCLCA  |d LQU  |d OCLCQ  |d S2H  |d OCLCO  |d VT2  |d OCLCO  |d OCL  |d OCLCQ  |d UPM  |d OCLCQ  |d OCLCO  |d OCLCL  |d SXB  |d OCLCQ 
020 |a 9780128026762  |q (electronic bk.) 
020 |a 0128026766  |q (electronic bk.) 
020 |z 9780128025819 
020 |z 0128025816 
035 |a (OCoLC)932289263  |z (OCoLC)932825393  |z (OCoLC)948810916  |z (OCoLC)1066447327  |z (OCoLC)1105192094  |z (OCoLC)1105575158  |z (OCoLC)1235839125 
245 0 0 |a Medical image recognition, segmentation and parsing :  |b machine learning and multiple object approaches /  |c edited by S. Kevin Zhou. 
264 1 |a Amsterdam :  |b Elsevier,  |c [2016] 
264 4 |c ©2016 
300 |a 1 online resource :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a The Elsevier and MICCAI society book series 
504 |a Includes bibliographical references and index. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of-the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image. You will learn how to: research challenges and problems in medical image recognition, segmentation and parsing of multiple objects; methods and theories for medical image recognition, segmentation and parsing of multiple objects; efficient and effective machine learning solutions based on big datasets; selected applications of medical image parsing using proven algorithms. --  |c Edited summary from book. 
505 0 |a Front Cover; Medical Image Recognition, Segmentation and Parsing: Machine Learning and Multiple Object Approaches; Copyright; Contents; Foreword; Acknowledgments; Contributors; Chapter 1: Introduction to Medical Image Recognition; 1.1 Introduction; 1.2 Challenges and Opportunities; 1.3 Rough-to-Exact Object Representation; 1.4 Simple-to-Complex Probabilistic Modeling; 1.4.1 Chain Rule; 1.4.2 Bayes' Rule and the Equivalence of Probabilistic Modelingand Energy-Based Method; 1.4.3 Practical Medical Image Recognition, Segmentation, and Parsing Algorithms. 
505 8 |a 1.5 Medical Image Recognition Using Machine Learning Methods1.5.1 Object Detection and Context; 1.5.2 Machine Learning Methods; 1.5.2.1 Classification; 1.5.2.2 Regression; 1.6 Medical Image Segmentation Methods; 1.6.1 Simple Image Segmentation Methods; 1.6.2 Active Contour Method; 1.6.3 Variational Methods; 1.6.4 Level Set Methods; 1.6.5 Active Shape Models and Active Appearance Models; 1.6.6 Graph Cut Method; 1.7 Conclusions; Recommended Notations; Notes; References; Part 1: AutomaticRecognition and DetectionAlgorithms; Chapter 2: A Survey of Anatomy Detection; 2.1 Introduction. 
505 8 |a 2.2 Methods for Detecting an Anatomy2.2.1 Classification-Based Detection Methods; 2.2.1.1 Boosting detection cascade; 2.2.1.2 Probabilistic boosting tree; 2.2.1.3 Randomized decision forest; 2.2.1.4 Exhaustive search to handle pose variation; 2.2.1.5 Parallel, pyramid, and tree structures; 2.2.1.6 Network structure: Probabilistic boosting network; 2.2.1.7 Marginal space learning; 2.2.1.8 Probabilistic, hierarchical, and discriminant framework; 2.2.1.9 Multiple instance boosting to handle inaccurate annotation; 2.2.2 Regression-Based Detection Methods; 2.2.2.1 Shape regression machine. 
505 8 |a 2.2.2.2 Hough forest2.2.3 Classification-Based vs Regression-Based Object Detection; 2.3 Methods for Detecting Multiple Anatomies; 2.3.1 Classification-Based Methods; 2.3.1.1 Discriminative anatomical network; 2.3.1.2 Active scheduling; 2.3.1.3 Submodular detection; 2.3.1.4 Integrated detection network; 2.3.2 Regression-Based Method: Regression Forest; 2.3.3 Combining Classification and Regression: Context Integration; 2.4 Conclusions; References; Chapter 3: Robust Multi-Landmark Detection Based on Information Theoretic Scheduling; 3.1 Introduction; 3.2 Literature Review; 3.3 Methods. 
505 8 |a 3.3.1 Problem Statement3.3.2 Scheduling Criterion Based on Information Gain; 3.3.3 Monte-Carlo Simulation Method for the Evaluation of Information Gain; 3.3.4 Implementation; Learning-based landmark detection; Spatial correlation across landmarks; 3.4 Applications; 3.4.1 Automatic View Identification of Radiographs; 3.4.2 Auto-Alignment for MR Knee Scan Planning; 3.4.3 Auto-Navigation for Anatomical Measurement in CT; 3.4.4 Automatic Vertebrae Labeling; 3.4.5 Virtual Attenuation Correction of Brain PET Images; 3.4.6 Bone Segmentation in MR for PET-MR Attenuation Correction; 3.5 Conclusion. 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Imaging systems in medicine. 
650 0 |a Machine learning. 
650 0 |a Image reconstruction. 
650 0 |a Pattern recognition systems. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Zhou, S. Kevin,  |e editor. 
776 0 8 |i Print version:  |z 0128025816  |z 9780128025819  |w (OCoLC)919014709 
830 0 |a Elsevier and MICCAI Society book series. 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpMIRSPML2/medical-image-recognition?kpromoter=marc  |y Full text