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Shape Analysis of the Human Brain University of Louisville ThinkIR: The University of Louisville's Institutional Repository Electronic Theses and Dissertations 5-2015 Shape analysis of the human brain. Matthew Joseph Nitzken 1987- University of Louisville Follow this and additional works at: https://ir.library.louisville.edu/etd Part of the Electrical and Computer Engineering Commons Recommended Citation Nitzken, Matthew Joseph 1987-, "Shape analysis of the human brain." (2015). Electronic Theses and Dissertations. Paper 2067. https://doi.org/10.18297/etd/2067 This Doctoral Dissertation is brought to you for free and open access by ThinkIR: The University of Louisville's Institutional Repository. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of ThinkIR: The University of Louisville's Institutional Repository. This title appears here courtesy of the author, who has retained all other copyrights. For more information, please contact [email protected]. SHAPE ANALYSIS OF THE HUMAN BRAIN By Matthew Joseph Nitzken B.S., University of Louisville, 2009 M.Eng., University of Louisville, 2010 A Dissertation Submitted to the Faculty of the J.B. Speed School of Engineering at the University of Louisville in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Electrical Engineering Department of Electrical and Computer Engineering University of Louisville Louisville, Kentucky May 2015 Copyright 2015 by Matthew Joseph Nitzken ALL RIGHTS RESERVED SHAPE ANALYSIS OF THE HUMAN BRAIN By Matthew Joseph Nitzken B.S., University of Louisville, 2009 M.Eng., University of Louisville, 2010 A Dissertation Approved on April 20, 2015 by the following Dissertation Committee Dissertation Director Dr. Ayman S. El-Baz, Ph.D. Co-Director Dr. Tamer Inanc, Ph.D. Dr. Manuel Casanova, M.D. Dr. Olfa Nasraoui, Ph.D. Dr. Jacek M. Zurada, Ph.D. ii DEDICATION Sometimes our light goes out but is blown into flame by another human being. Each of us owes deepest thanks to those who have rekindled this light. - Albert Schweitzer This dissertation is dedicated to Edward W. Scharre, and my parents, Joseph A. Nitzken and Katherine S. Nitzken. iii ACKNOWLEDGMENTS I want to give my deepest thanks to Dr. Ayman El-Baz for his hours of patience and assis- tance in helping me during my studies at the University of Louisville. Thanks to his generous knowledge and help during my time at U of L, I have been able to complete all of the tasks that I set out to finish. It has been a great honor to work with him. I would like to extend my sincere thanks to all of my committee members, Dr. Tamer Inanc, Dr. Manuel Casanova, Dr. Olfa Nasraoui, and Dr. Jacek M. Zurada, who have been a tremendous help during my doctoral studies. I also would like to thank the BioImaging Laboratory, and all of its members, who I have worked with for many years, and who have helped me on occasions to numerous to count. Finally I want to profusely thank my loved ones, family, and friends. They have provided me with inspiration and years of support during this degree program, and throughout life itself. I cannot thank them enough for giving me the opportunities to dream, allowing me to pursue the impossible, and then providing me the loving support to never give up. Above all, they are ultimately responsible for the work I present here, and all my future endeavors. iv ABSTRACT Shape Analysis of the Human Brain Matthew Joseph Nitzken April 20, 2015 Autism is a complex developmental disability that has dramatically increased in preva- lence, having a decisive impact on the health and behavior of children. Methods used to de- tect and recommend therapies have been much debated in the medical community because of the subjective nature of diagnosing autism. In order to provide an alternative method for understanding autism, the current work has developed a 3-dimensional state-of-the-art shape based analysis of the human brain to aid in creating more accurate diagnostic assessments and guided risk analyses for individuals with neurological conditions, such as autism. Methods: The aim of this work was to assess whether the shape of the human brain can be used as a reliable source of information for determining whether an individual will be diagnosed with autism. The study was conducted using multi-center databases of magnetic resonance images of the human brain. The subjects in the databases were analyzed using a series of algorithms consisting of bias correction, skull stripping, multi-label brain segmenta- tion, 3-dimensional mesh construction, spherical harmonic decomposition, registration, and classification. The software algorithms were developed as an original contribution of this dis- sertation in collaboration with the BioImaging Laboratory at the University of Louisville Speed School of Engineering. The classification of each subject was used to construct diagnoses v and therapeutic risk assessments for each patient. Results: A reliable metric for making neurological diagnoses and constructing therapeutic risk assessment for individuals has been identified. The metric was explored in populations of individuals having autism spectrum disorders, dyslexia, Alzheimers disease, and lung cancer. Conclusion: Currently, the clinical applicability and benefits of the proposed software approach are being discussed by the broader community of doctors, therapists, and parents for use in improving current methods by which autism spectrum disorders are diagnosed and understood. vi TABLE OF CONTENTS DEDICATION ................................................................................. iii ACKNOWLEDGMENTS...................................................................... iv ABSTRACT ................................................................................... v 1 INTRODUCTION1 1.1 The Human Brain ...................................................................... 1 1.2 Magnetic Resonance Imaging......................................................... 5 2 DEFINING AUTISM 11 2.1 Introduction............................................................................. 11 2.2 History of Autism Spectrum Disorders ................................................ 12 2.3 Neuropathology of Autism ............................................................. 14 2.4 Prevalence of Autism .................................................................. 18 2.5 Importance of Early Detection......................................................... 20 2.6 Existing Methods for Detecting Autism................................................ 21 3 SURVEY OF SHAPE ANALYSIS 25 3.1 Introduction............................................................................. 25 3.2 Medial Axis and Skeletal Analysis..................................................... 29 3.3 Geodesic Distances.................................................................... 34 3.4 Procrustes Analysis.................................................................... 39 vii TABLE OF CONTENTS TABLE OF CONTENTS 3.5 Deformable Models .................................................................... 43 3.6 Spherical Harmonics................................................................... 48 3.7 Morphometry........................................................................... 54 3.8 Additional Methods..................................................................... 58 3.8.1 Distance Mapping...................................................................... 59 3.8.2 Entropy-based Particle Systems ...................................................... 60 3.8.3 Graph Matching........................................................................ 60 3.8.4 Homologous Modeling................................................................. 61 3.8.5 Laplace-Beltrami....................................................................... 62 3.8.6 Reeb Graph ............................................................................ 63 3.8.7 Spectral Matching...................................................................... 64 3.8.8 Symmetry Analysis .................................................................... 65 3.8.9 Volumetric Analysis .................................................................... 66 3.9 Discussion.............................................................................. 66 3.9.1 Research Challenges.................................................................. 66 3.9.2 Comparisons and Trends.............................................................. 68 3.10 Summary of Shape Analysis .......................................................... 70 4 SIGHT FRAMEWORK 71 4.1 Introduction............................................................................. 71 4.2 Skull Stripping.......................................................................... 74 4.2.1 Bias Correction......................................................................... 74 4.2.2 BET Skull Stripping .................................................................... 75 4.2.3 Visual Appearance-Guided Iso-Surfaces ............................................. 76 4.2.4 First-Order Visual Appearance (P(gjm)) ............................................. 77 4.2.5 Second-Order Visual Appearance (P(m))............................................ 79 viii TABLE OF CONTENTS TABLE OF CONTENTS 4.2.6 Skull Stripping Results................................................................. 81 4.3 Segmentation .........................................................................
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