Title :
A tool for the quantitative spatial analysis of complex cellular systems
Author :
Fernandez-Gonzalez, R. ; Barcellos-Hoff, M.H. ; Ortiz-de-Solorzano, Carlos
Author_Institution :
Life Sci. Div., Univ. of California, Berkeley, CA, USA
Abstract :
Spatial events largely determine the biology of cells, tissues, and organs. In this paper, we present a tool for the quantitative spatial analysis of heterogeneous cell populations, and we show experimental validation of this tool using both artificial and real (mammary gland tissue) data, in two and three dimensions. We present the refined relative neighborhood graph as a means to establish neighborhood between cells in an image while modeling the topology of the tissue. Then, we introduce the M function as a method to quantitatively evaluate the existence of spatial patterns within one cell population or the relationship between the spatial distributions of multiple cell populations. Finally, we show a number of examples that demonstrate the feasibility of our approach.
Keywords :
biological tissues; cellular biophysics; graph theory; complex cellular system; mammary gland tissue data; neighborhood graph; quantitative spatial analysis; spatial distribution; tissue topology; Biochemistry; Biological tissues; Breast cancer; Cells (biology); Ducts; Laboratories; Mammary glands; Optical microscopy; Stem cells; Topology; Mammary gland; multiscale analysis; optical microscopy; quantitative biology; spatial distribution; tissue topology; Algorithms; Animals; Artificial Intelligence; Cells, Cultured; Computer Simulation; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Mammary Glands, Animal; Mammary Glands, Human; Mice; Microscopy, Confocal; Models, Biological; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Software;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2005.852466
