Advances in Computerized Analysis in Clinical and Medical Imaging [electronic resource].
- New York : CRC Press LLC, 2019.
- 1 online resource (281 pages)
Description based upon print version of record. 9.15 Feature Extraction
Cover; Half Title; Title Page; Copyright Page; Table of Contents; Preface; About the Editors; Contributors; 1. A New Biomarker for Alzheimer's Based on the Hippocampus Image Through the Evaluation of the Surface Charge Distribution; 1.1 Introduction; 1.2 Earlier Detection of Alzheimer's Disease; 1.3 Database ADNI; 1.4 Preprocessing; 1.5 Region of Interest; 1.6 Proposed Modeling and Tool; 1.7 Mathematical Background; 1.8 Results; 1.9 Conclusion; References; 2. Independent Vector Analysis of Non-Negative Image Mixture Model for Clinical Image Separation; 2.1 Background and Driving Forces 2.2 Diseases Diagnosed Using CXR2.3 Non-Negative Blind Image Separation; 2.4 Mixture of Non-Negative Sources Model for Image Separation Task; 2.5 Convex Divergence IPA Framework; 2.6 Experimental Setups; 2.7 Conclusion; References; 3. Rationalizing of Morphological Renal Parameters and eGFR for Chronic Kidney Disease Detection; 3.1 Introduction; 3.2 Typical GFR Estimation Methods Used; 3.3 Kidney Morphology Toward eGFR; 3.4 Endorsing Factors toward Image-Based GFR Estimation; 3.5 Conclusion; References 4. Human Computer Interface for Neurodegenerative Patients Using Machine Learning Algorithms4.1 Introduction; 4.2 Background; 4.3 Protocol and Signal Acquisition; 4.4 Signal Classification; 4.5 Result; 4.6 Conclusion; References; 5. Smart Mobility System for Physically Challenged People; 5.1 Introduction: Background; 5.2 Methodology; 5.3 Image Processing Module; 5.4 Motor Control Module; 5.5 Results and Discussions; 5.6 Summary; References; 6. DHS: The Cognitive Companion for Assisted Living of the Elderly; 6.1 Introduction; 6.2 Assisted Living Robots; 6.3 Companion Robots 6.4 Proposed Work: DHS Solution for All Needs in Elderly Care6.5 Conclusion and Future Work; References; 7. Raspberry Pi Based Cancer Cell Detection Using Segmentation Algorithm; 7.1 Introduction; 7.2 Related Work; 7.3 K-Nearest Neighbor Matching Algorithm; 7.4 Hardware Design; 7.5 Experimental Results; 7.6 Performance Measures; 7.7 Conclusion; References; 8. An AAC Communication Device for Patients with Total Paralysis; 8.1 Introduction; 8.2 Related Work; 8.3 Proposed System; 8.3.3 Advantages and Applications; 8.4 Tests and Results; 8.5 Conclusion; References 9. Case Studies on Medical Diagnosis Using Soft Computing Techniques9.1 Introduction; 9.2 Case Study 1: Detection of Heart Failure Parameters Using 2D Echocardiographic Images Using Artificial Neural Networks; 9.3 Heart Physiology; 9.4 Methodology; 9.5 Feature Extraction; 9.6 Artificial Neural Network Training; 9.7 Additive Gaussian Noise; 9.8 Input Image; 9.9 Artificial Neural Network Training; 9.10 Conclusion; 9.11 Case Study 2: Detection of Lung Cancer from CT Thoracic Images Using Hybrid Soft Computing Technique; 9.12 Overview of the Work; 9.13 Preprocessing; 9.14 Morphological Operations
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.