Advances in Computerized Analysis in Clinical and Medical Imaging

Advances in Computerized Analysis in Clinical and Medical Imaging book is devoted for spreading of knowledge through the publication of scholarly research, primarily in the fields of clinical & medical imaging. The types of chapters consented include those that cover the development and implementation of algorithms and strategies based on the use of geometrical, statistical, physical, functional to solve the following types of problems, using medical image datasets: visualization, feature extraction, segmentation, image-guided surgery, representation of pictorial data, statistical shape analysis, computational physiology and telemedicine with medical images. This book highlights annotations for all the medical and clinical imaging researchers’ a fundamental advances of clinical and medical image analysis techniques. This book will be a good source for all the medical imaging and clinical research professionals, outstanding scientists, and educators from all around the world for network of knowledge sharing. This book will comprise high quality disseminations of new ideas, technology focus, research results and discussions on the evolution of Clinical and Medical image analysis techniques for the benefit of both scientific and industrial developments. Features: Research aspects in clinical and medical image processing Human Computer Interaction and interface in imaging diagnostics Intelligent Imaging Systems for effective analysis using machine learning algorithms Clinical and Scientific Evaluation of Imaging Studies Computer-aided disease detection and diagnosis Clinical evaluations of new technologies Mobility and assistive devices for challenged and elderly people This book serves as a reference book for researchers and doctoral students in the clinical and medical imaging domain including radiologists. Industries that manufacture imaging modality systems and develop optical systems would be especially interested in the challenges and solutions provided in the book. Professionals and practitioners in the medical and clinical imaging may be benefited directly from authors’ experiences.

Table of Contents:
1. A New Biomarker for Alzheimer’s Based on the Hippocampus Image Through the Evaluation of the Surface Charge Distribution [Aldo A. Belardi, Fernandho de O. Freitas, Rodrigo P. Bechelli, and Rodrigo G. G. Piva] 2. Independent Vector Analysis of Non-Negative Image Mixture Model for Clinical Image Separation [D. Sugumar, P. T. Vanathi, Xiao-Zhi Gao, Felix Erdmann Ott, and M. S. Aezhisai Vallavi] 3. Rationalizing of Morphological Renal Parameters and eGFR for Chronic Kidney Disease Detection [Deepthy Mary Alex, D. Abraham Chandy, and Anand Paul] 4. Human Computer Interface for Neurodegenerative Patients Using Machine Learning Algorithms [S. Ramkumar, G. Emayavaramban, J. Macklin Abraham Navamani, R. Renuga Devi, A. Prema, B. Booba, and P. Sriramakrishnan] 5. Smart Mobility System for Physically Challenged People [S. Sundaramahalingam, B. V. Manikandan, K. Banumalar, and S. Arockiaraj] 6. DHS: The Cognitive Companion for Assisted Living of the Elderly [R. Krithiga] 7. Raspberry Pi Based Cancer Cell Detection Using Segmentation Algorithm [S. Yogashri, S. Jayanthy, and C. Narendhar] 8. An AAC Communication Device for Patients with Total Paralysis [Oshin R. Jacob and Sundar G. Naveen] 9. Case Studies on Medical Diagnosis Using Soft Computing Techniques [Mary X. Anitha, Lina Rose, Aldrin Karunaharan, and Anand Pushparaj J.] 10. Alzheimer’s Disease Classification Using Machine Learning Algorithms [S. Naganandhini, P. Shanmugavadivu, A. Asaithambi, and M. Mohammed Mansoor Roomi] 11. Fetal Standard Plane Detection in Freehand Ultrasound Using Multi Layered Extreme Learning Machine [S. Jayanthi Sree and C. Vasanthanayaki] 12. Earlier Prediction of Cardiovascular Disease Using IoT and Deep Learning Approaches [R. Sivaranjani and N. Yuvaraj] 13. Analysis of Heart Disease Prediction Using Various Machine Learning Techniques [M. Marimuthu, S. Deivarani, and R. Gayathri] 14. Computer-Aided Detection of Breast Cancer on Mammograms: Extreme Learning Machine Neural Network Approach [Jayesh George M. and Perumal Sankar S.] 15. Deep Learning Segmentation Techniques for Checking the Anomalies of White Matter Hyperintensities in Alzheimer’s Patients [Antonitta Eileen Pious and Sridevi Unni] 16. Investigations on Stabilization and Compression of Medical Videos [D. Raveena Judie Dolly, D. J. Jagannath, and R. Anup Raveen Jaison] 17. An Automated Hybrid Methodology Using Firefly Based Fuzzy Clustering for Demarcation of Tissue and Tumor Region in Magnetic Resonance Brain Images [Saravanan Alagarsamy, Kartheeban Kamatchi, and Vishnuvarthanan Govindaraj] 18. A Risk Assessment Model for Alzheimer’s Disease Using Fuzzy Cognitive Map [S. Meenakshi Ammal and L. S. Jayashree] 19. Comparative Analysis of Texture Patterns for the Detection of Breast Cancer Using Mammogram Images [J. Shiny Christobel and J. Joshan Athanesious] 20. Analysis of Various Color Models for Endoscopic Images [Caren Babu, Anand Paul, and D. Abraham Chandy] 21. Adaptive Fractal Image Coding Using Differential Scheme for Compressing Medical Images [P. Chitra, M. Mary Shanthi Rani, and V. Sivakumar]