Application of 3-D digital deconvolution to optically sectioned images for improving the automatic analysis of fluorescent-labeled tumor specimens

The analysis of fluorescent stained clusters of cells has been improved by recording multiple images of the same microscopic scene at different focal planes and then applying a three dimensional (3-D) out of focus background subtraction algorithm. The algorithm significantly reduced the out of focus signal and improved the spatial resolution. The method was tested on specimens of 10 μm diameter (φ) beads embedded in agarose and on a 5 μm breast tumor section labeled with a fluorescent DNA stain. The images were analyzed using an algorithm for automatically detecting fluorescent objects. The proportion of correctly detected in focus beads and breast nuclei increased from 1/8 to 8/8 and from 56/104 to 81/104 respectively after processing by the subtraction algorithm. Furthermore, the subtraction algorithm reduced the proportion of out of focus relative to in focus total intensity detected in the bead images from 51% to 33%. Further developments of these techniques, that utilize the 3-D point spread function (PSF) of the imaging system and a 3-D segmentation algorithm, should result in the correct detection and precise quantification of virtually all cells in solid tumor specimens. Thus the approach should serve as a highly reliable automated screening method for a wide variety of clinical specimens.