RECONSTRUCTION AND DISPLAY OF CURVILINEAR OBJECTS FROM OPTICAL SECTION DATA USING 3-D CURVE-FITTING ALGORITHMS

Biological objects resembling filaments are often highly elongated whi le presenting a small cross-sectional area, Examination of such object s requires acquisition of images from regions large enough to contain entire objects, but at sufficiently high resolution to resolve individ ual filaments. These requirements complicate the application of conven tional optical sectioning and volume reconstruction techniques. For ex ample, objective lenses used to acquire images of entire filaments or filament networks may lack sufficient depth (Z) resolution to localize filament cross-sections along the optical axis, Because volume recons truction techniques consider only the information represented by a sin gle volume element (voxel), views of filament networks reconstructed f rom images obtained at low Z-resolution will not accurately represent filament morphology, A possible solution to these problems is to simul taneously utilize all available information on the path of an object b y fitting 3-D curves through data points localized in 2-D images, Here , we present an application of this approach to the reconstruction of microtubule networks from 2-D optical sections obtained using confocal microscopy, and to synthesized curves which have been distorted using a simple mathematical model of optical sectioning artefacts, Our resu lts demonstrate that this strategy can produce high resolution 3-D vie ws of filamentous objects from a small number of optical sections.