Contact informationPlease contact Tarjei S. Hveem for more information
Visualisation of textural features
In this project, texture features will be visualised in nuclei in 2D and 3D, to improve the understanding of which biological mechanisms Nucleotyping describe.
We have developed a series of texture properties with documented diagnostic and/or prognostic value, and for some of these, we have a superior understanding of the type of functional chromatin changes they describe.
However, we still have a long way to go before we are able to understand in detail the association between structural and functional changes in the chromatin. One way is to identify all nuclei with a given property value in a histological section. For this purpose, we have started the project MicroTracker (see below). Another is to visualize each texture property directly in the nucleus to be measured by staining or marking the part of the chromatin giving the texture property of interest.
We will further develop the method for all properties from the entropy matrix. This is includes 9 properties which interpret different characteristics of the matrix. We will investigate different methods for visualizing properties to best illustrate which information they describe. In addition to understanding what we describe, this is a valuable study for improving understanding of how different window sizes and number of gray tones change the result.
Texture features used in Nucleotyping have demonstrated their prognostic value for several cancer types. However, what the texture features describe biologically is not well understood. In order to examine this further we will develop methods to visualize which parts of the nuclei are decisive for the discriminating effect. The next question to answer is then why these parts are crucial, i.e. which biological functions do these compartments have? A query system for studying nuclei in 2D sections and identifying which are crucial to the classification, given a classifier, will also be developed. This will make it possible to visualize which nuclei and which areas of the tumor are decisive for a given classification.
This text was last modified: 08.02.2016