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Background@#To properly utilize the sectioned images in a Visible Monkey dataset, it is essential to segment the images into distinct structures. This segmentation allows the sectioned images to be compiled into two-dimensional or three-dimensional software packages to facilitate anatomy and radiology education, and allows them to be used in experiments involving electromagnetic radiation. The purpose of the present study was to demonstrate the potential of the sectioned images using the segmented images. @*Methods@#Using sectioned images of a monkey's entire body, 167 structures were segmented using Adobe Photoshop. The segmented images and sectioned images were packaged into the browsing software. Surface models were made from the segmented images using Mimics. Volume models were made from the sectioned images and segmented images using MRIcroGL. @*Results@#In total, 839 segmented images of 167 structures in the entire body of a monkey were produced at 0.5-mm intervals (pixel size, 0.024 mm; resolution, 8,688 × 5,792; color depth, 24-bit color; BMP format). Using the browsing software, the sectioned images and segmented images were able to be observed continuously and magnified along with the names of the structures. The surface models of PDF file were able to be handled freely using Adobe Reader. In the surface models, the space information of all segmented structures was able to be identified using Sim4Life. On MRIcroGL, the volume model was able to be browsed and sectioned at any angle with real color. @*Conclusion@#Browsing software, surface models, and volume models are able to be produced based on the segmentation of the sectioned images. These will be helpful for students and researchers studying monkey anatomy and radiology, as well as for biophysicists examining the effects of electromagnetic radiation.
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PURPOSE: To evaluate the relationship between depressive symptoms and health care costs in outpatients with chronic medical illnesses in Korea, we screened for depressive symptoms in 1,118 patients with a chronic medical illness and compared the severity of somatic symptoms and health care costs. PATIENTS AND METHODS: Data were compared between outpatients with depressive symptoms and those without depressive symptoms. Depression and somatic symptoms were measured by Zung's Self-rating Depression Scale (SDS) and Patient Health Questionnaire (PHQ)-15, respectively. We also investigated additional data related to patients' health care costs (number of visited clinical departments, number of visits made per patients, and health care costs). A total of 468 patients (41.9%) met the criteria for depressive disorder. RESULTS: A high rate of severe depressive symptoms was found in elderly, female and less-educated patients. A positive association between the severity of somatic symptoms and depressive symptoms was also identified. The effects of depressive symptoms in patients with chronic illnesses on three measures of health services were assessed by controlling for the effects of demographic variables and the severity of somatic symptoms. We found that the effects of depressive symptoms on the number of visited departments and number of visits made per patients were mediated by the severity of somatic symptoms. However, for health care costs, depressive symptoms had a significant main effect. Furthermore, the effect of gender on health care costs is moderated by the degree of a patient's depressive symptoms. CONCLUSION: In summary, there is clearly a need for increased recognition and treatment of depressive symptoms in outpatients with chronic medical illnesses.