GemIdent Examples

The following are some examples of GemIdent in action. For a more intimate introduction, please watch the demo videos (previous page).


The raw photograph (left), a superimposed mask showing the pixel classification results (center), and finally the photograph is marked with the centroids of the object of interest - the oranges (right)


The raw microscopic image of a stained lymph node (left) from the Kohrt study, a superimposed mask showing the pixel classification results (center), and finally the image is marked with the centroids of the object of interest - the cancer nuclei (right)


The raw microscopic image of a stained lymph node (top left), the superimposed pixel mask (top right) and the final marked image (center). This example illustrates GemIdent's ability to find multiple phenotypes in the same image. In this case, there are three: the red cancer cells (marked with green stars), the brown T-cells (marked with yellow stars), and other cell nuclei (marked with cyan stars) which aren't specifically stained.


The command-line data analysis and visualization interface in action analyzing results of a classification of a lymph node from the Kohrt study. The histogram displays the distribution of distances from T-cells to neighboring cancer cells. The binary image of cancer membrane is the result of an pixel-only classification. The open PDF document is the autogenerated report of the analysis which includes a thumbnail view of the entire lymph node, counts and Type I error rates for all phenotypes, as well as a transcript of the analyses performed.

©2007 Board of Trustees of Leland Stanford Junior University. All Rights Reserved.
SEO Services by DONE! SEO