IMAGING AND MODELING FROM SERIAL MICROSCOPIC SECTIONS FOR THE STUDY OF ANATOMY

A system is considered for segmenting noisy intensity images and conse quent three-dimensional object reconstruction from a set of planar con tours. A new semiautomatic method for the extraction of contours from a sequence of cross-sectional images based on an active contour model (AGM) is proposed. The dynamic ACM proceeds along the sequence of cros s-sections following a non-rigid motion, in accordance with the organ boundary. Image texture information is also employed in the model. Pro blems associated with topological reconstruction from planar contours are addressed, and several criteria promoting semi-automatic topologic al reconstruction are introduced, The proposed system is successfully applied to the processing of real data related to animal embryonic org ans, proving that the system allows detailed modelling of irregular ob jects. The reconstructed models can be observed in wire-frame, solid, transparent or stereoscopic semi-transparent format. The human-compute r interaction implemented in the procedure assists with problems of fe ature identification and object manipulation about an arbitrary axis.