System for analysis of microscopic data using graphs

1. A system for analysis of microscopic image data acquired from biological cells, the system comprising a processor to:

read the image data;

determine a plurality of vertices, wherein each of the vertices represents a location of an entity of interest within a region of interest of the image data;

generate a plurality of graphs, wherein for each of the graphs, the generation of the respective graph comprises generating a plurality of edges, wherein each of the edges has two of the plurality of vertices associated therewith;

wherein for each of the graphs, the generating of the respective graph comprises:

determining for a pair of the vertices whether to generate an edge associated with the pair depending on whether a distance between the vertices of the pair according to a predefined metric is smaller than a threshold (R 1 , R 2 ) which is predefined for the respective graph;

wherein the predefined thresholds (R 1 , R 2 ) of the graphs are different from each other;

wherein each of the graphs comprises the plurality of edges generated for the respective graph and the plurality of vertices;

identify, for each of the graphs and depending on the edges generated for the respective graph, one or more vertex sets, each of which comprising one or more of the plurality of vertices; and to

generate, for each of the graphs, a number of the identified vertex sets;

determine a difference between two of the determined numbers of identified vertex sets of different graphs; and to

classify and/or to rate at least one tissue portion contained in the region of interest, a cell contained in the region of interest, a group of cells contained in the region of interest and/or the region of interest depending on the determined difference.

2. The system of claim 1 , wherein the processor is further configured to determine a sum of the determined numbers of identified vertex sets over all or over a portion of the generated graphs.

3. The system of claim 2 , wherein the processor is further configured to classify and/or to rate at least one tissue portion contained in the region of interest, a cell contained in the region of interest, a group of cells contained in the region of interest and/or the region of interest depending on the determined sum.

4. The system of claim 1 , wherein the generation of the graphs comprises: generating a Voronoi diagram depending on the vertices; wherein the Voronoi diagram comprises exactly one Voronoi region for each of the vertices; and wherein each of the graphs is generated based on the Voronoi diagram.

5. The system of claim 4 , wherein each of the graphs is constructed from a respective radius-bounded Voronoi diagram, in which each of the Voronoi regions is spatially bounded by a same maximum Radius (R3); wherein each of the graphs has a different maximum Radius (R3).

6. The system of claim 1 , wherein the processor is further configured to classify and/or to rate at least one tissue portion contained in the region of interest, a cell contained in the region of interest, a group of cells contained in the region of interest and/or the region of interest depending on the determined numbers of generated vertex sets.

7. The system of claim 1 , wherein for each of the graphs, the generation of the plurality of edges comprises: determining for each pair of the vertices, whether or not to generate an edge.

8. The system of claim 1 wherein for each of the graphs:

a) each of the identified vertex sets consists of one vertex or more vertices so that each pair thereof is connected by one or more of the edges of the graph; and

b) the identified vertex sets are mutually unconnected by the edges of the graph.

9. The system of claim 1 , wherein the system comprises an scanner to: receive a sample, which comprises the cells; and to image the cells.

10. A method of analyzing microscopic data acquired from biological cells, wherein the analysis is performed using a processor, the method comprising:

reading using the processor, the image data;

determining using the processor, a plurality of vertices, wherein each of the vertices represents a location of an entity of interest within a region of interest of the image data;

generating, using the processor, a plurality of graphs, wherein for each of the graphs, the generation of the respective graph comprises generating a plurality of edges, wherein each of the edges has two of the plurality of vertices associated therewith;

wherein for each of the graphs, the generating of the respective graph comprises:

determining for a pair of the vertices whether to generate an edge associated with the pair depending on whether a distance between the vertices of the pair according to a predefined metric is smaller than a threshold (R 1 , R 2 ) which is predefined for the respective graph;

wherein the predefined thresholds (R 1 , R 2 ) of the graphs are different from each other;

wherein each of the graphs comprises the plurality of edges generated for the respective graph and the plurality of vertices;

identifying, using the processor, for each of the graphs and depending on the edges generated for the respective graph, one or more vertex sets, each of which comprising one or more of the plurality of vertices; and

generating, using the processor, for each of the graphs, a number of the identified vertex sets;

determining, using the processor, a difference between two of the determined numbers of identified vertex sets of different graphs; and

classifying and/or rating, using the processor, at least one tissue portion contained in the region of interest, a cell contained in the region of interest, a group of cells contained in the region of interest and/or the region of interest depending on the determined difference.

11. A non-transitory computer readable medium having stored thereon a program for analyzing microscopic data acquired from biological cells, wherein the program, when being executed by a processor causes the processor to carry out:

reading the image data;

determining a plurality of vertices, wherein each of the vertices in the plurality represents a location of an entity of interest within a region of interest of the image data;

generating, using the processor, a plurality of graphs, wherein the generation of the respective graphs comprises generating a plurality of edges, wherein each of the edges has two of the plurality of vertices associated therewith;

wherein for each of the graphs, the generating of the respective graph comprises:

determining for a pair of the vertices whether to generate an edge associated with the pair depending on whether a distance between the vertices of the pair according to a predefined metric is smaller than a threshold (R 1 , R 2 ) which is predefined for the respective graph

wherein the predefined thresholds (R 1 , R 2 ) of the graphs are different from each other;

wherein each of the graphs comprises the plurality of edges generated for the respective graph and the plurality of vertices;

identifying, for each of the graphs and depending on the edges generated for the respective graph, one or more vertex sets, each of which comprising one or more of the plurality of vertices; and

generating, for each of the graphs, a number of the identified vertex sets;

determining a difference between two of the determined numbers of identified vertex sets of different graphs; and

classifying and/or rating at least one tissue portion contained in the region of interest, a cell contained in the region of interest, a group of cells contained in the region of interest and/or the region of interest depending on the determined difference.