A novel machine vision application for analysis and visualization of confocal microscopic images

In this paper, a novel machine vision application is presented for analyzing and visualizing confocal microscopy images of biological preparations. The proposed system is divided into three subsystems: a 3D curved surface extraction subsystem that generates 3D surfaces passing through selected key points in confocal image stacks; a 2D image projection subsystem that produces a flattened projection of the extracted curved surface; and an image mosaic subsystem that concatenates a series of image projections to form a view of an entire biological preparation. A combination of cubic interpolation and boundary matching is employed to reconstruct the 3D curved surface that passes through selected key points. The projection process integrates data fidelity and local smoothness constraints, producing a color or intensity projection along the desired 3D surface. Registration is achieved by aligning and minimizing the sum of the squared distances (SSD) between the intensities of the corresponding pixels. Two biological applications of the proposed system are reported to illustrate how the vision system could aid in biological research.