A Framework for the Visualization of Cross Sectional Data in Biomedical Research

In this paper we present the framework of our reconstruction and visualization system for planar cross sectional data. Three-dimensional reconstructions are used to analyze the patterns and functions of dying (apoptotic) and dividing (mitotic) cells in the early developing nervous system. Reconstructions are built-up from high resolution scanned, routinely stained histological serial sections (section thickness = 1 μm), which provide optimal conditions to identify individual cellular events in complete embryos. We propose new sophisticated filter algorithms to preprocess images for subsequent contour detection. Fast active contour methods with enhanced interaction functionality and a new memory saving approach can be applied on the pre-filtered images in order to semiautomatically extract inner contours of the embryonic brain and outer contours of the surface ectoderm. We present a novel heuristic reconstruction algorithm, which is based on contour and chain matching, and which was designed to provide good results very fast in the majority of cases. Special cases are solved by additional interaction. After optional postprocessing steps, surfaces of the embryo as well as cellular events are simultaneously visualized.