Savita Gupta – författare

Advances in Computational Techniques for Biomedical Image Analysis: Methods and Applications focuses on post-acquisition challenges such as image enhancement, detection of edges and objects, analysis of shape, quantification of texture and sharpness, and pattern analysis. It discusses the archiving and transfer of images, presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing. It examines various feature detection and segmentation techniques, together with methods for computing a registration or normalization transformation.

Advances in Computational Techniques for Biomedical Image Analysis: Method and Applications is ideal for researchers and post graduate students developing systems and tools for health-care systems.

Covers various challenges and common research issues related to biomedical image analysis Describes advanced computational approaches for biomedical image analysis Shows how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Explores a range of computational algorithms and techniques, such as neural networks, fuzzy sets, and evolutionary optimization Explores cloud based medical imaging together with medical imaging security and forensics

Advances in Computational Techniques for Biomedical Image Analysis: Methods and Applications focuses on post-acquisition challenges such as image enhancement, detection of edges and objects, analysis of shape, quantification of texture and sharpness, and pattern analysis. It discusses the archiving and transfer of images, presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing. It examines various feature detection and segmentation techniques, together with methods for computing a registration or normalization transformation.Advances in Computational Techniques for Biomedical Image Analysis: Method and Applications is ideal for researchers and post graduate students developing systems and tools for health-care systems.- Covers various challenges and common research issues related to biomedical image analysis- Describes advanced computational approaches for biomedical image analysis- Shows how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc.- Explores a range of computational algorithms and techniques, such as neural networks, fuzzy sets, and evolutionary optimization- Explores cloud based medical imaging together with medical imaging security and forensics

Artificial intelligence and Explainable computational intelligence are continuously reshaping the detection, monitoring and data-rich diagnostics in neurological disorders. This book brings together recent advances in neuro-focused AI systems, biomedical signal interpretation, multi-modal analytics and explainable AI. The chapters progress from foundational perspectives on AI-enabled neurological and biomedical data to recent machine learning and deep learning frameworks for ECG and EEG-based disease screening, and finally toward assistive and translational technologies such as sign language recognition, virtual reality interventions, regenerative neurology, and cancer AI analytics.This book:Offers a detailed perspective on explainable AI-based systems for neurological diagnosis, and clinical decision support.Discusses key physiological and neural biomarkers, including heart rate variability, skin conductance, entropy analytics, ECG, and EEG signals.Includes recent AI model designs from wearable sensor analytics and brain connectivity for assistive systems.Includes machine learning approaches for conditions such as Alzheimer’s, epilepsy (seizure prediction and surgery outcomes), and other neurological disorders.Explores translational technologies and therapies, for different neuro disorders, along with multi-modal AI insights for early tumor detection.The book is suitable for research scholars, clinicians, and postgraduate students working in biomedical signal analysis, neuro-AI modelling, wearable diagnostics, and intelligent assistive systems.