Supervised Segmentation of Visible Human Data with Image Analogies

Abstract-- We present a new application of the Image Analogies algorithm to be used for image segmentation. Our approach requires supervised training data, so we apply it to the domain of labeling human anatomical data. In the Visible Human Project, expert anatomists are overwhelmed with high-resolution images to analyze. We propose that the anatomist can work in conjunction with our approach, letting the machine segment 80% of the images, and requiring that the expert segment only every fifth image.

• Type: Conference
• Year: 2004
• Where: ICAI
• Authors: James B. Lackey, Michael D. Colagrosso
• Keywords: Human Anatomical Data, ICAI 2004, ICAI 2007, Supervised Training Data, Visible Human Project