Automated contour extraction using a multi-scale approach

Abstract

Many image registration methods use surface of head or brain to estimate rotation and translation parameters. The surface is usually characterized by a set of edge or contour points extracted from cross-sectional images. Automatic extraction of contour points is complicated by discontinuity of edges in the back of eyes and ears and sometimes by an inadequate field of view. The authors have developed an automated method for contour extraction that connects discontinuities using a multi-scale pyramid. Steps of the method are: (1) Contour points are found by an edge-tracking algorithm; (2) A multi-scale pyramid of contour points is constructed; (3) Contour points of reduced images are found; (4) From the continuous contour found at the lowest scale, contour points at a higher scale are found; (5) Step 4 is repeated until contour points at the highest resolution (original image) are found. The method runs fast and has successfully been used for MRI and CT image registration. The authors illustrate the method and its performance using MRI and CT images of the human brain. >