Neurological Disorders and Imaging Physics, Volume 3 : Application to Autism Spectrum Disorders and Alzheimer’s

This volume covers the state-of-the-art topics that investigate two significant neurological disorders: the Autism Spectrum disorder (ASD) and Alzheimer's disease (AD) not only from the theoretical perspective but also focuses on the practicalaspects. The materials are presented in a way that can be beneficial to both advanced and layman readers PRELIMS.pdf Preface Acknowledgments Editor biographies Ayman El-Baz Jasjit S Suri List of contributors CH001.pdf Chapter 1 Machine learning applications to recognize autism and Alzheimer’s disease 1.1 Introduction 1.2 Brain disorders 1.2.1 Autism spectrum disorder (ASD) 1.2.2 Alzheimer’s disease (AD) 1.2.3 Mild cognitive impairment 1.3 Deep learning 1.3.1 ASD and deep learning 1.3.2 Alzheimer’s and deep learning 1.4 Conclusion References CH002.pdf Chapter 2 Neuropathology and neuroimaging of Alzheimer’s disease Abbreviations 2.1 Alzheimer’s disease: history, concept, clinical picture, and neurobiology 2.1.1 Brief history and concept 2.1.2 Clinical presentation 2.1.3 Neurobiology and physiopathology of Alzheimer’s disease 2.1.4 Clinical and physiopathological feature assessment 2.2 Biomarkers 2.2.1 CSF biomarkers 2.2.2 Neuroimaging biomarkers 2.3 Understanding AD progression through structural imaging 2.3.1 Mapping AD neuropathology through neuronal circuits: what is the point? 2.3.2 Cortical myelination throughout life 2.3.3 Models of the neuropathological progression of AD 2.3.4 Hypothetical models of neurodegeneration 2.3.5 Understanding the biophysical properties of DTI 2.4 Conclusions References CH003.pdf Chapter 3 Retinal imaging in Alzheimer’s disease 3.1 Introduction 3.2 Lipofuscin hypothesis of AD 3.3 OCT and FAF in retinal diseases 3.3.1 SD-OCT and FAF in diagnosing AD 3.4 Misfolded proteins in the retina 3.5 Cryo-electron microscopy 3.6 Retinal imaging of misfolded proteins 3.7 Curcumin 3.8 AMD and AD 3.9 Glaucoma and AD 3.10 Alpha-synuclein in AD 3.11 Early diagnosis of AD 3.12 Biomarkers in AD 3.13 Discussion References CH004.pdf Chapter 4 Clinically relevant depression and risk of Alzheimer’s disease in the elderly: meta-analysis of cohort studies 4.1 Introduction 4.2 Methods 4.2.1 Search strategy 4.2.2 Study selection 4.2.3 Data extraction 4.2.4 Quality assessment 4.2.5 Statistical analysis 4.3 Results 4.3.1 Study selection 4.3.2 Description of included studies 4.3.3 Effect estimation of AD risk based on depression 4.3.4 The risk of publication bias 4.3.5 Influence analysis 4.3.6 Population attributable fraction 4.4 Discussion 4.4.1 Main results 4.4.2 Comparison with previous studies 4.4.3 Strengths and limitations 4.4.4 Pathogenic hypotheses 4.4.5 Clinical implications 4.4.6 Public health implications 4.5 Conclusion References CH005.pdf Chapter 5 The implications of genetic factors in autism spectrum disorder and Alzheimer’s disease 5.1 Autism spectrum disorder 5.2 Alzheimer’s disease 5.2.1 Introduction 5.2.2 Clinical assessment 5.2.3 Risk and protective factors 5.2.4 Neuropathological changes 5.2.5 Genetics of AD References CH006.pdf Chapter 6 Nuclear neurology of autism spectrum disorder 6.1 Introduction 6.1.1 Imaging modalities 6.2 Specific neurochemical physiology 6.2.1 Dopaminergic neurotransmission 6.2.2 Serotoninergic neurotransmission 6.2.3 Serotonin synthesis 6.2.4 Serotonin transporter (SERT) 6.2.5 Serotonin (5-HT 2A) receptor 6.2.6 GABA 6.3 Basal physiology 6.3.1 Protein synthesis 6.3.2 Glucose metabolism 6.4 Regional cerebral blood flow 6.4.1 PET investigation 6.4.2 SPECT investigation 6.5 Conclusion References CH007.pdf Chapter 7 Ethylene and ammonia in neurobehavioral disorders 7.1 Introduction 7.2 Method 7.3 Volatile organic compounds in autism and schizophrenia 7.3.1 Schizophrenia 7.3.2 Autism 7.3.3 Ethylene in mental disorders 7.3.4 Ammonia in mental disorders 7.4 Results and discussion 7.4.1 Protocol for breath gas sampling from schizophrenic patients 7.4.2 Ethylene and ammonia assessment using LPAS from schizophrenic patients 7.4.3 Protocol for breath gas sampling from autistic young adults 7.4.4 Ethylene and ammonia assessment using LPAS in autistic young adults 7.5 Conclusions and future directions References CH008.pdf Chapter 8 The impact of stress on parental behavior following a diagnosis of autism 8.1 Parental stress and the ASD diagnosis 8.2 The potential effect of stress on parental treatment choices 8.2.1 The prevalence of fad treatments 8.3 Parents as the agents of behavioral change 8.4 Factors affecting parental involvement 8.4.1 Making parent training accessible 8.4.2 Focusing on the contingencies that maintain parents’ behaviors 8.5 Tying it all together: mitigating stress, selecting evidence-based treatments, and increasing parental involvement References CH009.pdf Chapter 9 Visual saliency for medical imaging and computer-aided diagnosis 9.1 Introduction 9.2 Visual saliency for medical image analysis 9.3 Saliency model for Alzheimer’s disease detection from structural MRI 9.3.1 Visual assessment of brain atrophy for AD diagnosis 9.3.2 AD saliency map generation Algorithm 1. STD map estimation 9.4 Visual interpretation of visual saliency 9.4.1 Region of interest detection and quantification 9.4.2 Comparison with state-of-the-art saliency models 9.5 AD classification using saliency maps 9.5.1 Proposed method 9.5.2 MRI data 9.5.3 Classification results 9.6 Conclusion Acknowledgement References CH010.pdf Chapter 10 The early diagnosis of Alzheimer’s disease using advanced biomedical engineering technology 10.1 Introduction 10.2 Literature review 10.3 Causes and effects of AD 10.4 Hallmarks of AD 10.5 The retina and AD 10.6 Tests for diagnosing AD 10.7 Early diagnosis of AD 10.8 Medical imaging techniques 10.9 Analysis of MRI and OCT images 10.9.1 Image acquisition 10.9.2 Pre-processing 10.9.3 Image segmentation 10.9.4 Image post-processing 10.9.5 Feature extraction 10.9.6 Feature selection 10.9.7 Classification 10.10 Discussion 10.11 Conclusion Acknowledgments References CH011.pdf Chapter 11 A local/regional computer aided system for the diagnosis of mild cognitive impairment 11.1 Introduction 11.2 Material and methods 11.2.1 Materials 11.2.2 Methods 11.3 Results 11.4 Discussion Acknowledgments References CH012.pdf Chapter 12 Identifying Alzheimer’s disease using feature reduction of GLCM and supervised classification techniques 12.1 Introduction 12.2 Related work 12.3 The proposed supervised-learning approach for AD identification 12.3.1 Voxel-based morphometric feature extraction 12.3.2 Texture feature extraction 12.3.3 Feature reduction 12.3.4 Classification 12.4 Experimental results and discussion 12.4.1 Dataset 12.4.2 Experimental work 12.5 Conclusion and future work References CH013.pdf Chapter 13 Current trends and considerations of Alzheimer’s disease 13.1 Introduction 13.2 Anatomical background 13.2.1 Neurological diseases 13.2.2 Neurodegenerative diseases 13.2.3 Alzheimer’s disease 13.3 Medical imaging modalities for AD 13.3.1 Radiology 13.3.2 Printed signals/waves 13.4 AD literature review 13.4.1 CAD system based studies 13.5 Discussion 13.5.1 Databases 13.5.2 Modalities 13.5.3 Applied techniques 13.5.4 Subjects 13.6 Conclusion References CH014.pdf Chapter 14 A noninvasive image-based approach toward an early diagnosis of autism 14.1 Introduction 14.2 Methods 14.2.1 Segmentation 14.2.2 Feature extraction 14.3 Experimental results and conclusions References CH015.pdf Chapter 15 Towards a robust CAD system for early diagnosis of autism using structural MRI 15.1 Introduction 15.2 Methods 15.2.1 Cx and CWM segmentation from MRI scans 15.2.2 Extraction of shape features 15.2.3 Deep fusion classification network (DFCN) 15.3 Experimental results and conclusions References CH016.pdf Chapter 16 Computational analysis techniques: a case study on fMRI for autism spectrum disorder 16.1 Introduction 16.2 Task based fMRI analysis 16.2.1 Building the design matrix 16.2.2 Multi level general linear model (GLM) in fMRI 16.2.3 GLM parameter estimates 16.2.4 Limitations of GLM for parameter estimation in fMRI analysis 16.3 RfMRI analysis 16.3.1 Principle components analysis in RfMRI analysis 16.3.2 Independent components analysis in RfMRI analysis 16.3.3 Restricted Boltzmann machines in RfMRI analysis 16.4 A case study of fMRI in autism 16.4.1 Task based fMRI findings in autism 16.4.2 Resting state fMRI findings in autism 16.5 Conclusions and future work References CH017.pdf Chapter 17 Autism diagnosis using task-based functional MRI 17.1 Introduction 17.2 Materials and methods 17.2.1 Data preprocessing 17.2.2 Multi level general linear model (GLM) in fMRI 17.2.3 Feature selection and classification 17.3 Experimental results and conclusion 17.3.1 Higher level analysis 17.3.2 Classification results 17.3.3 Conclusion and future work References "Autism spectrum disorder (ASD) and Alzheimer's disease (AD) are two significant neurological disorders, which represent the scope of this book. Both ASD and AD effect a significant number of the population and present themselves in numerous ways. This volume covers the state-of-the-art topics that investigate these two significant neurological disorders, not only from the theoretical perspective but also focuses on the practical aspects. The materials are presented in a way that can be beneficial to both advanced and layman readers. Several state-of-the-art machine learning techniques for the early diagnosis of ASD are presented in this book. Also, various studies are discussed to demonstrate the formation, cause, and medical treatments for the AD foetal disorder." -- Prové de l'editor Autism spectrum disorder (ASD) and Alzheimer's disease (AD) are two significant neurological disorders, which represent the scope of this book. Both ASD and AD affect a significant number of the population and present in numerous ways. This volume covers the state-of-the-art topics that investigate these two significant neurological disorders from a theoretical perspective and focuses on the practical aspects. Materials are presented in a way that can be beneficial to advanced and layman readers and several cutting-edge machine learning techniques for the early diagnosis of ASD are presented in this book. Also, various studies are discussed to demonstrate the formation, cause, and medical treatments for the AD foetal disorder.