Neurological disorders and imaging physics. Volume 3, Application to autism spectrum disorders and Alzheimer's / [edited by] Ayman El-Baz, Jasjit S. Suri.

Format:

Book

Contributor:

El-Baz, Ayman S., editor.

Suri, Jasjit S., editor.

Institute of Physics (Great Britain), publisher.

Series:

IOP ebooks. 2020 collection.

IOP ebooks. [2020 collection]

Language:

English

Subjects (All):

Central nervous system--Magnetic resonance imaging.

Central nervous system.

Central nervous system--Diseases--Diagnosis.

Alzheimer's disease--Magnetic resonance imaging.

Alzheimer's disease.

Autism spectrum disorders--Magnetic resonance imaging.

Autism spectrum disorders.

Magnetic resonance imaging.

Physical Description:

1 online resource (various pagings) : illustrations (some color).

Other Title:

Application to autism spectrum disorders and Alzheimer's.

Place of Publication:

Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2020]

System Details:

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.

text file

Biography/History:

Ayman El-Baz is a Professor, University Scholar, and Chair of the Bioengineering Department at the University of Louisville, Kentucky. Dr. El-Baz earned his BSc and MSc degrees in electrical engineering in 1997 and 2001, respectively. He earned his PhD in electrical engineering from the University of Louisville in 2006. Dr. El-Baz has 17 years of hands-on experience in the fields of bio-imaging modeling and non-invasive computer-assisted diagnosis systems. Jasjit S. Suri is an innovator, scientist, visionary, industrialist and an internationally known world leader in biomedical engineering. Dr. Suri has spent over 25 years in the field of biomedical engineering/devices and its management. In 2018, he was awarded the Marquis Life Time Achievement Award for his outstanding contributions and dedication to medical imaging and its management.

Summary:

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.

Contents:

1. Machine learning applications to recognize autism and Alzheimer's disease

1.1. Introduction

1.2. Brain disorders

1.3. Deep learning

1.4. Conclusion

2. Neuropathology and neuroimaging of Alzheimer's disease

2.1. Alzheimer's disease : history, concept, clinical picture, and neurobiology

2.2. Biomarkers

2.3. Understanding AD progression through structural imaging

2.4. Conclusions

3. Retinal imaging in Alzheimer's disease

3.1. Introduction

3.2. Lipofuscin hypothesis of AD

3.3. OCT and FAF in retinal diseases

3.4. 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

4. Clinically relevant depression and risk of Alzheimer's disease in the elderly : meta-analysis of cohort studies

4.1. Introduction

4.2. Methods

4.3. Results

4.4. Discussion

4.5. Conclusion

5. The implications of genetic factors in autism spectrum disorder and Alzheimer's disease

5.1. Autism spectrum disorder

5.2. Alzheimer's disease

6. Nuclear neurology of autism spectrum disorder

6.1. Introduction

6.2. Specific neurochemical physiology

6.3. Basal physiology

6.4. Regional cerebral blood flow

6.5. Conclusion

7. Ethylene and ammonia in neurobehavioral disorders

7.1. Introduction

7.2. Method

7.3. Volatile organic compounds in autism and schizophrenia

7.4. Results and discussion

7.5. Conclusions and future directions

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

8.3. Parents as the agents of behavioral change

8.4. Factors affecting parental involvement

8.5. Tying it all together : mitigating stress, selecting evidence-based treatments, and increasing parental involvement

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

9.4. Visual interpretation of visual saliency

9.5. AD classification using saliency maps

9.6. Conclusion

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

10.10. Discussion

10.11. Conclusion

11. A local/regional computer aided system for the diagnosis of mild cognitive impairment

11.1. Introduction

11.2. Material and methods

11.3. Results

11.4. Discussion

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

12.4. Experimental results and discussion

12.5. Conclusion and future work

13. Current trends and considerations of Alzheimer's disease

13.1. Introduction

13.2. Anatomical background

13.3. Medical imaging modalities for AD

13.4. AD literature review

13.5. Discussion

13.6. Conclusion

14. A noninvasive image-based approach toward an early diagnosis of autism

14.1. Introduction

14.2. Methods

14.3. Experimental results and conclusions

15. Towards a robust CAD system for early diagnosis of autism using structural MRI

15.1. Introduction

15.2. Methods

15.3. Experimental results and conclusions

16. Computational analysis techniques : a case study on fMRI for autism spectrum disorder

16.1. Introduction

16.2. Task based fMRI analysis

16.3. RfMRI analysis

16.4. A case study of fMRI in autism

16.5. Conclusions and future work

17. Autism diagnosis using task-based functional MRI

17.1. Introduction

17.2. Materials and methods

17.3. Experimental results and conclusion.

Notes:

"Version: 20191101"--Title page verso.

Includes bibliographical references.

Title from PDF title page (viewed on December 9, 2019).

Other Format:

Print version:

ISBN:

9780750317931

9781643276489

OCLC:

1130295076

Access Restriction:

Restricted for use by site license.