Object level association

Revision as of 03:53, 3 May 2009

In this page we give an overview of the distance map-based approach for defining object-level associations

Overview

We present a simple, yet general framework for object-level association between biological objects and/or elements present in the different channels of multi-channel images. The proposed object-level association framework assumes that any association rule is defined between two elements. The first one, which we call the reference element, is the segmented object (such as cells/nuclei) for which we want to quantify some associative relationships. The second element, which we call the target element, is a biologically meaningful element in a different channel. The target element does not have to be segmented or undergone under any kind of processing.

Two association examples are shown in Figure 1 below. In both examples, the reference element is a segmented cell nucleus. However, the target element in the first example (panel A) is a segmented blood vessel. Hence, association occurs between two segmented objects. In the second example (panel B), the target element is a molecular signal (yellow) that may surround some cell nuclei and available in a different channel.

Two association examples. Both examples use segmented nuclei as their reference elements but the target elements are a segmented blood vessel in (A), and a molecular signal from another channel (yellow) in (B).

An association rule is composed of two components. The first one defines the region of interest (ROI) associated with the reference elements and on which the associative measure is applied. The second component is an associative measure, which is a mathematical function defined on the regions of interest (ROI) of the reference elements, and used to quantify the associative relationship.

Running The Program

Sample Output