Preface properly inform decision making. Chapter 4(Medical Data visualization Toward Integrated Clinical Workstations) presents works related to the visualiz- ation of medical data. A survey of graphical metaphors (lists and tables, plots and charts, graphs and trees, and pictograms)is given, relating their use to convey clinical concepts. A discussion of portraying temporal, spatial, multidimensional nd causal relationships is provided, using the navigation of images as an example application. Methods to combine these visual components are illustrated, based on a definition of(task) context and user modeling, resulting in a means of creating an adaptive graphical user interface to accommodate the range of different user Part Ill, Documenting Imaging Findings, discusses techniques for automatically nt fro In Chapter 5( Characterizing Imaging Data), an introduction to medical image understanding is presented. Unlike standard image processing, techniques within medical imaging informatics focus on how imaging studies, alongside other clinical data, can be standardized and their content(automatically) extracted to guide medical decision making processes. Notably, unless medical images are standard- ized, quantitative comparisons across studies is subject to various sources of bias/ artifacts that negatively influence assessment. From the perspective of creating scientific-quality imaging databases, this chapter starts with the groundwork for understanding what exactly an image captures, and commences to outline the dif- ferent aspects encompassing the standardization process: intensity normalization denoising, and both linear and nonlinear image registration methods are covered Subsequently, a discussion of commonly extracted imaging features is given, divided amongst appearance-and shape-based descriptors. with the wide array of image features that can be computed, an overview of image feature selection and dimensionality reduction methods is provided. Lastly, this chapter concludes with a description of increasingly popular imaging-based anatomical atlases, detailing their construction and usage as a means for understanding population-based norms and differences arising due to a disease process Absent rigorous methods to automatically analyze and quantify image findings, radiology reports are the sole source of expert image interpretation. In point of fact, a large amount of information about a patient remains locked within clinical documents, and as with images, the concepts therein are not readily computer un- derstandable. Chapter 6(Natural Language Processing of Medical Reports) deals with the structuring and standardization of free-text medical reports via natural language processing(NLP). Issues related to medical NLP representation. computation, and evaluation are presented. An overview of the NLP task is first described to frame the problem, providing an analysis of past efforts and applica- tions of NLP. A sequence of subtasks is then related: structural analysis (e.g,section and sentence boundary detection), lexical analysis(e. g, logical word sequences, disambiguation, concept coding), phrasal chunking, and parsing are covered. For each subtask, a description of the challenges and the range of approaches are given to familiarize the reader with the field Core to informatics endeavors is a systematic method to organize both data and knowledge, representing original(clinical) observations, derived data, and conclu sions in a logical manner. Chapter 7(Organizing Observations: Data Models) describes the different types of relationships between healthcare entities, particularly focusing on those relations commonly encountered in medical imaging. Often inxii Preface properly inform decision making. Chapter 4 (Medical Data Visualization: Toward Integrated Clinical Workstations) presents works related to the visualiz￾ation of medical data. A survey of graphical metaphors (lists and tables; plots and charts; graphs and trees; and pictograms) is given, relating their use to convey clinical concepts. A discussion of portraying temporal, spatial, multidimensional, and causal relationships is provided, using the navigation of images as an example an adaptive graphical user interface to accommodate the range of different user goals involving patient data. Part III, Documenting Imaging Findings, discusses techniques for automatically extracting content from images and related data in order to objectify findings: ƒ In Chapter 5 (Characterizing Imaging Data), an introduction to medical image understanding is presented. Unlike standard image processing, techniques within medical imaging informatics focus on how imaging studies, alongside other clinical data, can be standardized and their content (automatically) extracted to guide medical decision making processes. Notably, unless medical images are standard￾ized, quantitative comparisons across studies is subject to various sources of bias/ artifacts that negatively influence assessment. From the perspective of creating scientific-quality imaging databases, this chapter starts with the groundwork for understanding what exactly an image captures, and commences to outline the dif￾ferent aspects encompassing the standardization process: intensity normalization; denoising; and both linear and nonlinear image registration methods are covered. Subsequently, a discussion of commonly extracted imaging features is given, divided amongst appearance- and shape-based descriptors. With the wide array of image features that can be computed, an overview of image feature selection and dimensionality reduction methods is provided. Lastly, this chapter concludes with a description of increasingly popular imaging-based anatomical atlases, detailing their construction and usage as a means for understanding population-based norms and differences arising due to a disease process. ƒ Absent rigorous methods to automatically analyze and quantify image findings, radiology reports are the sole source of expert image interpretation. In point of fact, a large amount of information about a patient remains locked within clinical documents; and as with images, the concepts therein are not readily computer un￾derstandable. Chapter 6 (Natural Language Processing of Medical Reports) deals with the structuring and standardization of free-text medical reports via natural language processing (NLP). Issues related to medical NLP representation, computation, and evaluation are presented. An overview of the NLP task is first described to frame the problem, providing an analysis of past efforts and applica￾tions of NLP. A sequence of subtasks is then related: structural analysis (e.g., section and sentence boundary detection), lexical analysis (e.g., logical word sequences, disambiguation, concept coding), phrasal chunking, and parsing are covered. For each subtask, a description of the challenges and the range of approaches are given to familiarize the reader with the field. ƒ Core to informatics endeavors is a systematic method to organize both data and knowledge, representing original (clinical) observations, derived data, and conclu￾sions in a logical manner. Chapter 7 (Organizing Observations: Data Models) describes the different types of relationships between healthcare entities, particularly focusing on those relations commonly encountered in medical imaging. Often in on a definition of (task) context and user modeling, resulting in a means of creating application. Methods to combine these visual components are illustrated, based