Ahmad Fadzil Mohamad Hani – författare

Optical imaging is a rapidly emerging imaging technique that has been successfjully translated into biomedical applications ranging from clinical diagnosis to molecular biology. This book includes an introductory section to explore various optical imaging devices and their functionality and roles for biomedical applications such as dermatology and ophthalmology. Recent developments as exemplified with the authors research are explored in detail. In depth discussion of other disease conditions and their diagnosis with optical imaging techniques are also covered.

Based on hospital clinical trials examining the use of signal and image processing techniques, Surface Imaging for Biomedical Applications bridges the gap between engineers and clinicians. This text offers a thorough analysis of biomedical surface imaging to medical practitioners as it relates to the diagnosis, detection, and monitoring of skin conditions and disease. Written from an engineer’s perspective, the book discusses image acquisition methods, image processing, and pattern recognition techniques. It focuses on a variety of techniques used in recent years for image processing and pattern recognition (principal component analysis, independent component analysis, singular value decomposition, texture modeling, inverse model analysis, polynomial surface fitting, and classification techniques), and considers interventional and non-invasive procedures used to diagnose skin-related disease. It examines the biological causation of four skin disorders (psoriasis, vitiligo, ulcer, and acne), provides basic terminologies in surface imaging, and details the outcome of various clinical observations and other research. It also details numerous measurement parameters related to surface imaging (body surface, skin color, tissue characteristic, thickness, roughness, volume of skin, and retinal changes). Discusses the development of a psoriasis severity measurement toolProvides material on assessing segmented repigmentation areas in vitiligo patients via VT-ScanIntroduces a volume ulcer assessment using non-invasive 3D imagingPresents an automated system for acne grading that is based on capturing the images of various body parts using the DSLR cameraIncludes the MATLAB® codes for various pattern recognition techniques applied during the assessment/measurement at the end of each chapter This interdisciplinary reference highlights the importance of disease diagnosis and monitoring, and is suitable for medical practitioners, biomedical engineers, and core image processing researchers.

Based on hospital clinical trials examining the use of signal and image processing techniques, Surface Imaging for Biomedical Applications bridges the gap between engineers and clinicians. This text offers a thorough analysis of biomedical surface imaging to medical practitioners as it relates to the diagnosis, detection, and monitoring of skin conditions and disease. Written from an engineer’s perspective, the book discusses image acquisition methods, image processing, and pattern recognition techniques. It focuses on a variety of techniques used in recent years for image processing and pattern recognition (principal component analysis, independent component analysis, singular value decomposition, texture modeling, inverse model analysis, polynomial surface fitting, and classification techniques), and considers interventional and non-invasive procedures used to diagnose skin-related disease. It examines the biological causation of four skin disorders (psoriasis, vitiligo, ulcer, and acne), provides basic terminologies in surface imaging, and details the outcome of various clinical observations and other research. It also details numerous measurement parameters related to surface imaging (body surface, skin color, tissue characteristic, thickness, roughness, volume of skin, and retinal changes). Discusses the development of a psoriasis severity measurement toolProvides material on assessing segmented repigmentation areas in vitiligo patients via VT-ScanIntroduces a volume ulcer assessment using non-invasive 3D imagingPresents an automated system for acne grading that is based on capturing the images of various body parts using the DSLR cameraIncludes the MATLAB® codes for various pattern recognition techniques applied during the assessment/measurement at the end of each chapter This interdisciplinary reference highlights the importance of disease diagnosis and monitoring, and is suitable for medical practitioners, biomedical engineers, and core image processing researchers.