Automated image analysis technologies for biological 3D light microscopy

Abstract

Techniques for three-dimensional (3D) light microscopy of a wide variety of biological specimens are rapidly maturing. The next advances are to improve image contrast, make image resolution as isotropic as possible, and perform quantitative analysis. This article discusses methods of automatic image analysis and blind deconvolution to compensate for the microscope's point-spread function (impulse response). Special emphasis is given to quantitative analysis based on adaptive segmentation, the results of which can be used to quantify and trace individual structures, and to montage high-resolution fields as well as the results of image analysis on these fields into a wide-area view with an associated computer database representation. We exploit the specific advantages accruing from the 3D nature of the data to achieve new capabilities not possible with 2D imaging. Fundamental and practical challenges in this area and our progress to date including automated segmentation, cell counting, neuron tracing, mosaic synthesis, “blind” deconvolution of large 3D images, and high-speed computation are presented. © 1997 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 8, 240–254, 1997