Medical Imaging Informatics provides an overview of this growing discipline. This volume explores the technologies and algorithms that comprise this field, as well as the application of medical imaging informatics to subsequently improve healthcare research.

Medical Imaging Informatics provides an overview of this growing discipline, which stems from an intersection of biomedical informatics, medical imaging, computer science and medicine. Supporting two complementary views, this volume explores the fundamental technologies and algorithms that comprise this field, as well as the application of medical imaging informatics to subsequently improve healthcare research. Clearly written in a four part structure, this introduction follows natural healthcare processes, illustrating the roles of data collection and standardization, context extraction and modeling, and medical decision making tools and applications.

Medical Imaging Informatics identifies core concepts within the field, explores research challenges that drive development, and includes current state-of-the-art methods and strategies.

Illustrates the objective use of imaging alongside other clinical information to advance the understanding of disease In-depth coverage of methods to improve image study interpretation Provides a comprehensive discussion of the role of structured reporting, medical natural language processing and ontology development efforts within the area of imaging informatics Offers a unique look into medical decision making and development of (imaging-based) disease models

Zusammenfassung
Medical Imaging Informatics provides an overview of this growing discipline, which stems from an intersection of biomedical informatics, medical imaging, computer science and medicine.

Inhalt
Performing the Imaging Exam.- A Primer on Imaging Anatomy and Physiology.- Integrating Imaging into the Patient Record.- Information Systems & Architectures.- Medical Data Visualization: Toward Integrated Clinical Workstations.- Documenting Imaging Findings.- Characterizing Imaging Data.- Natural Language Processing of Medical Reports.- Organizing Observations: Data Models.- Toward Medical Decision Making.- Disease Models, Part I: Graphical Models.- Disease Models, Part II: Querying & Applications.- Evaluation.