GemIdent

For example, color image segmentation of: GemIdent also packages data analysis tools to investigate spatial relationships among the objects identified.

GemIdent was developed at Stanford University by Adam Kapelner from June, 2006 until January, 2007 in the lab of Dr. Peter Lee under the tutelage of Professor Susan Holmes.

Therefore, the user must do a substantial amount of work first supplying the relevant colors, then pointing out examples of the objects or regions themselves as well as negatives (training set creation).

[5] 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,[2] 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) This example illustrates GemIdent's ability to find multiple phenotypes in the same image: the raw microscopic image of a stained lymph node (top left) from the Kohrt study,[2] a superimposed mask showing the pixel classification results (top right), and finally the image marked with the centroids of the objects of interest - the cancer nuclei (in green stars), the T-cells (in yellow stars), and non-specific background nuclei (in cyan stars).

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.