3D structural analysis from biological confocal images

Laser confocal imaging gives the capability of obtaining 3D images of biological and other microscopic structures using optical slicing. This eliminates one of the problems in classical scene understanding where a 3D to 2D mapping and subsequent loss of information has taken place. In this paper we discuss the implementation of a multi-dimensional image analysis system used to extract and analyse biological structures in confocal images. The image processing and structural analysis techniques are implemented as a set of knowledge sources or tools which operate on the input image to successively refine and segment the image. These knowledge sources in the system consists of a combination of simple edge/surface detectors and multi-level thresholding to generate the initial segmentation. This segmentation is further refined by a set of more complex knowledge sources such as 3D morphological operators, a hierarchical refinement scheme, specialized feature detectors, active contour models and by the use of external knowledge. The analysis tools operate on the segmented image to obtain morphometrical parameters such as surface area, volume, position and orientation of structures of interest and to generate overall statistical properties of these parameters. A visualization subsystem lets the user to manipulate and selectively display the results of segmentation.