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The purpose of this paper is to describe a framework for evaluating image segmentation algorithms. Image segmentation consists of object recognition and delineation. For evaluating segmentation methods, three factors-precision (reliability), accuracy (validity), and efficiency (viability)-need to be considered for both recognition and delineation. To assess precision, we need to choose a figure of merit, repeat segmentation considering all sources of variation, and determine variations in figure of merit via statistical analysis. It is impossible usually to establish true segmentation. Hence, to assess accuracy, we need to choose a surrogate of true segmentation and proceed as for precision. In determining accuracy, it may be important to consider different 'landmark' areas of the structure to be segmented depending on the application. To assess efficiency, both the computational and the user time required for algorithm training and for algorithm execution should be measured and analyzed. Precision, accuracy, and efficiency factors have an influence on one another. It is difficult to improve one factor without affecting others. Segmentation methods must be compared based on all three factors, as illustrated in an example wherein two methods are compared in a particular application domain. The weight given to each factor depends on application. q

The purpose of this paper is to describe a framework for evaluating image segmentation algorithms. Image segmentation consists of object recognition and delineation. For evaluating segmentation methods, three factors -precision (reproducibility), accuracy (agreement with truth), and efficiency (time taken) -need to be considered for both recognition and delineation. To assess precision, we need to choose a figure of merit (FOM), repeat segmentation considering all sources of variation, and determine variations in FOM via statistical analysis. It is impossible usually to establish true segmentation. Hence, to assess accuracy, we need to choose a surrogate of true segmentation and proceed as for precision. To assess efficiency, both the computational and the user time required for algorithm and operator training and for algorithm execution should be measured and analyzed. Precision, accuracy, and efficiency are interdependent. It is difficult to improve one factor without affecting others. Segmentation methods must be compared based on all three factors. The weight given to each factor depends on application.

Previous studies of young children have failed to demonstrate adult-like odor preferences in children less than 5 years old. To test whether these results may have been due to inappropriate methods or to stimulus sets that were too limited in range to capture discriminations, a forced-choice procedure embedded in a simple game was used to contrast 3-year-olds' (n = 16) and adults' (n = 17) hedonic reactions to 9 odorants. Subjects indicated liking an odor by pointing to one puppet and disliking an odor by pointing to another puppet. Analyses revealed essentially the same pattern of preferences in both groups. In general, the odorant was a much better predictor of its hedonic quality than was the age of the subject. However, children and adults did differ in their ratings of some odors, and response patterns indicated that children may be more sensitive than adults to some odorants (e.g., the steroid androstenone). These data indicate that the predominant view that adult-like odor preferences and aversions do not exist until between 5 and 7 years of age must be reevaluated.

In this chapter, the author describes integrating the teaching of the basic sciences, clinical sciences, and biopsychosocial issues in medical education as part of the curricular reform efforts initiated by schools that participated in The Robert Wood Johnson Foundation's project "Preparing: Physicians for the Future: Program in Medical Education." The author focuses on the approaches the eight schools adopted, the challenges they encountered, and the lessons they learned in attempting to implement more integrated curricula. Integration was promoted both within and among various components of medical education. For example, in some cases discipline-based courses in the basic sciences were replaced with interdisciplinary courses. Further, efforts were made both to bring clinical relevance to the basic sciences and to strengthen basic science in the clinical years. All the schools also promoted the study of the humanities and biopsychosocial sciences throughout the curriculum. The author describes problems encountered in these endeavors, resources needed to support interdisciplinary courses, the benefits of integration, and common lessons learned by the eight schools.