Automatic Hough Transform-Based 3D Segmentation of Cell Nuclei in Thick Tissue Sections

Abstract

Combining pathology, which reports the structural features of individual cells and their spatial organi-zation in a tissue specimen, with molecular biology techniques (immunocytochemistry and fluores-cence in situ hybridization, FISH) for detecting the distribution of specific molecular species in individual cells is a powerful approach for gaining insight into the underlying disease mechanisms of carcinogenesis. This approach requires analysis of thick (>20 ¼m) tissue sections in which cells are preserved intact within the context of their environment. 3D (confocal) microscope image acquisition followed by 3D image analysis (IA) for extracting quantitative information are then used for quantita-tive analysis of tissue features such as nuclear and/or cell volume, shape, total fluorescence or FISH signal number. An essential component of the IA is detection of the individual cells, or their nuclei since many molecular species of interest are localized within the nucleus (e.g. genetic aberrations). We present here a completely automatic, 3D algorithm for this task, which based on the Hough transform (HT).