Internet of Things (IoT) brings telemedicine a new chance. This enables the specialist to consult the patient�s condition despite\nthe fact that they are in different places. Medical image segmentation is needed for analysis, storage, and protection of medical\nimage in telemedicine. Therefore, a variety of methods have been researched for fast and accurate medical image segmentation.\nPerforming segmentation in various organs, the accurate judgment of the region is needed in medical image. However, the removal\nof region occurs by the lack of information to determine the region in a small region. In this paper,we researched howto reconstruct\nsegmentation region in a small region in order to improve the segmentation results.We generated predicted segmentation of slices\nusing volume data with linear equation and proposed improvementmethod for small regions using the predicted segmentation. In\norder to verify the performance of the proposed method, lung region by chest CT images was segmented. As a result of experiments,\nvolume data segmentation accuracy rose from 0.978 to 0.981 and from 0.281 to 0.187 with a standard deviation improvement\nconfirmed.
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