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Proceedings Paper

Feature based registration of fluorescent LSCM imagery using region centroids
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Paper Abstract

We present a novel semi-automated registration technique for 3D volume reconstruction from fluorescent laser scanning confocal microscope (LSCM) imagery. The developed registration procedure consists of (1) highlighting segmented regions as salient feature candidates, (2) defining two region correspondences by a user, (3) computing a pair of region centroids, as control points for registration, and (4) transforming images according to estimated transformation parameters determined by solving a set of linear equations with input control points. The presented semi-automated method is designed based on our observations that (a) an accurate point selection is much harder for a human than an accurate region (segment) selection, (b) a centroid selection of any region is less accurate by a human than by a computer, and (c) registration based on structural shape of a region rather than on intensity-defined point is more robust to noise and to morphological deformation of features across stacks. We applied the method to image mosaicking and image alignment registration steps and evaluated its performance with 20 human subjects on LSCM images with stained blood vessels. Our experimental evaluation showed significant benefits of automation for 3D volume reconstruction in terms of achieved accuracy, consistency of results and performance time. In addition, the results indicate that the differences between registration accuracy obtained by experts and by novices disappear with an advanced automation while the absolute registration accuracy increases.

Paper Details

Date Published: 29 April 2005
PDF: 12 pages
Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.595699
Show Author Affiliations
Sang-Chul Lee, Univ. of Illinois/Urbana-Champaign (United States)
Peter Bajcsy, Univ. of Illinois/Urbana-Champaign (United States)


Published in SPIE Proceedings Vol. 5747:
Medical Imaging 2005: Image Processing
J. Michael Fitzpatrick; Joseph M. Reinhardt, Editor(s)

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