Dermoscopy is a noninvasive skin imaging technique that uses optical magnification and either liquid immersion or cross-polarized lighting to make subsurface structures more easily visible when compared to conventional clinical images. It allows for the identification of dozens of morphological features that are particularly important in identifying malignant melanoma. Dermoscopy Image Analysis summarizes the state of the art of the computerized analysis of dermoscopy images. The book begins by discussing the influence of color normalization on classification accuracy and then: Investigates gray-world, max-RGB, and shades-of-gray color constancy algorithms, showing significant gains in sensitivity and specificity on a heterogeneous set of images Proposes a new color space that highlights the distribution of underlying melanin and hemoglobin color pigments, leading to more accurate classification and border detection results Determines that the latest border detection algorithms can achieve a level of agreement that is only slightly lower than the level of agreement among experienced dermatologists Provides a comprehensive review of various methods for border detection, pigment network extraction, global pattern extraction, streak detection, and perceptually significant color detection Details a computer-aided diagnosis (CAD) system for melanomas that features an inexpensive acquisition tool, clinically meaningful features, and interpretable classification feedback Presents a highly scalable CAD system implemented in the MapReduce framework, a novel CAD system for melanomas, and an overview of dermatological image databases Describes projects that made use of a publicly available database of dermoscopy images, which contains 200 high-quality images along with their medical annotations Dermoscopy Image Analysis not only showcases recent advances but also explores future directions for this exciting subfield of medical image analysis, covering dermoscopy image analysis from preprocessing to classification.

This book brings together the most current thinking and research on educator stress and how education systems can support quality teachers and quality education. It adopts an occupational health perspective to examine the problem of educator stress and presents theory-driven intervention strategies to reduce stress load and support educator resilience and healthy school organizations. The book provides an international perspective on key challenges facing educators such as teacher stress, teacher retention, training effective teachers, teacher accountability, cyber-bullying in schools, and developing healthy school systems. Divided into four parts, the book starts out by introducing and defining the problem of educator stress internationally and examining educator stress in the context of school, education system, and education policy factors. Part I includes chapters on educator mental health and well-being, stress-related biological vulnerabilities, the relation of stress to teaching self-efficacy, turnover in charter schools, and the role of culture in educator stress. Part II reviews the main conceptual models that explain educator stress while applying an occupational health framework to education contexts which stresses the role of organizational factors, including work organization and work practices. It ends with a proposal of a dynamic integrative theory of educator stress, which highlights the changing nature of educator stress with time and context. Part III starts with the definition of what constitute healthy school organizations as a backdrop to the following chapters which review the application of occupational health psychology theories and intervention approaches to reducing educator stress, promoting teacher resources and developing healthy school systems. Chapters include interventions at the individual, individual-organizational interface and organizational levels. Part III ends with a chapter addressing cyber-bullying, a new challenge affecting schools and teachers. Part IV discusses the implications for research, practice and policy in education, including teacher training and development. In addition, it presents a review of methodological issues facing researchers on educator stress and identifies future trends for research on this topic, including the use of ecological momentary assessment in educator stress research. The editors' concluding comments reflect upon the application of an occupational health perspective to advance research, practice and policy directed at reducing stress in educators, and promoting teacher and school well-being.

Dermoscopy is a noninvasive skin imaging technique that uses optical magnification and either liquid immersion or cross-polarized lighting to make subsurface structures more easily visible when compared to conventional clinical images. It allows for the identification of dozens of morphological features that are particularly important in identifying malignant melanoma. Dermoscopy Image Analysis summarizes the state of the art of the computerized analysis of dermoscopy images. The book begins by discussing the influence of color normalization on classification accuracy and then: Investigates gray-world, max-RGB, and shades-of-gray color constancy algorithms, showing significant gains in sensitivity and specificity on a heterogeneous set of images Proposes a new color space that highlights the distribution of underlying melanin and hemoglobin color pigments, leading to more accurate classification and border detection results Determines that the latest border detection algorithms can achieve a level of agreement that is only slightly lower than the level of agreement among experienced dermatologists Provides a comprehensive review of various methods for border detection, pigment network extraction, global pattern extraction, streak detection, and perceptually significant color detection Details a computer-aided diagnosis (CAD) system for melanomas that features an inexpensive acquisition tool, clinically meaningful features, and interpretable classification feedback Presents a highly scalable CAD system implemented in the MapReduce framework, a novel CAD system for melanomas, and an overview of dermatological image databases Describes projects that made use of a publicly available database of dermoscopy images, which contains 200 high-quality images along with their medical annotations Dermoscopy Image Analysis not only showcases recent advances but also explores future directions for this exciting subfield of medical image analysis, covering dermoscopy image analysis from preprocessing to classification.