Automatic recognition of cells (ARC) for 3D images of C. elegans
RECOMB'08 Proceedings of the 12th annual international conference on Research in computational molecular biology
Efficient and robust shape retrieval from deformable templates
ISoLA'12 Proceedings of the 5th international conference on Leveraging Applications of Formal Methods, Verification and Validation: applications and case studies - Volume Part II
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Motivation:Caenorhabditis elegans, a roundworm found in soil, is a widely studied model organism with about 1000 cells in the adult. Producing high-resolution fluorescence images of C.elegans to reveal biological insights is becoming routine, motivating the development of advanced computational tools for analyzing the resulting image stacks. For example, worm bodies usually curve significantly in images. Thus one must ‘straighten’ the worms if they are to be compared under a canonical coordinate system. Results: We develop a worm straightening algorithm (WSA) that restacks cutting planes orthogonal to a ‘backbone’ that models the anterior–posterior axis of the worm. We formulate the backbone as a parametric cubic spline defined by a series of control points. We develop two methods for automatically determining the locations of the control points. Our experimental methods show that our approaches effectively straighten both 2D and 3D worm images. Contact: pengh@janelia.hhmi.org Supplementary information: The example data sets and programs are available upon request.