Abstract
As a noted topic of life science, brain research is aimed to solve how people learn and memorize. In Drosophila brain, it is discovered that several brain controlling genes are very similar to human’s, and so as how they function. Thus, Drosophila brain plays an important role for studying simple neural networks and can help figure out such main functions as learning and memory.In order to study the main structures and functions of Drosophila brain, confocal microscope is used to image fluorescent brain slices, and reconstruct individual 3-D brain models, which from the platform that biologists place neural networks and other structures into. Due to the objectiveness, rather than taking any one model as a standard, it’s better to average all individual models. The averaged brain model is a standard model for image database.The average method works well on most convex regions but encounters some problems on concave regions. The averaged concave region is filled up because of feature location, orientation and size variations, which need to be adjusted before averaging process.A curve averaging and local warping method to solve this problem is presented in this study. A Bezier curve is drawn manually near the featured spots. After auto fitting to each brain model, the individual Bezier curves is produced. In order to keep the desired feature during performing Bezier curve averaging, calculate the Bezier curve moving vectors, and apply brain surface model a local deformation according to the Bezier curve moving. The proposed algorithm can perform a warping on local region to the average shape. Furthermore, it works well on keeping the desired feature after overall averaging process.