System, method, and kit for processing a magnified image of biological material to identify components of a biological object

Abstract

A system, method and kit for processing an original image of biological material to identify certain components of a biological object by locating the biological object in the image, enhancing the image by sharpening components of interest in the object, and applying a contour-finding function to the enhanced image to create a contour mask. The contour mask may be processed to yield a segmented image divided by structural units of the biological material.

1 . A computerized method for analyzing a magnified image of cells, comprising the microscopy system-executed steps of:
 finding shapes of structures in cells in the image by a process adapted for the shapes;   finding contours of the structures based on the shapes; and,   generating a mask of the contours.   
     
     
         2 . The method of  claim 1 , wherein the shapes are irregular rings. 
     
     
         3 . The method of  claim 2 , wherein the irregular rings are cell membrane outlines. 
     
     
         4 . The method of  claim 1 , wherein the shapes are substantially circular. 
     
     
         5 . The method of  claim 4 , wherein the substantially circular shapes are lipid droplet outlines. 
     
     
         6 . A computerized method for analyzing an original magnified image of cells, comprising:
 generating shapes of lipid droplets in cells in the original image by at least one function adapted for finding rounded shapes in an image;   generating markers associated with the lipid droplets;   generating a mask of lipid droplet outlines in response to the shapes and the markers; and   measuring structures of lipid droplets in the original image with the mask.   
     
     
         7 . The method of  claim 6 , wherein generating shapes of lipid droplets includes generating shapes of small lipid droplets by a first function and generating shapes of large lipid droplets by a second function and generating an aggregate image of the shapes by the union of results produced by the first and second functions. 
     
     
         8 . The method of  claim 7 , wherein generating a mask of lipid droplets includes generating a mask by a watershed algorithm. 
     
     
         9 . The method of  claim 8 , further including measuring one or more cell features associated with the lipid droplets. 
     
     
         10 . A kit for visualization of cell membrane activation, comprising:
 a program product storing a program for a membrane activation image processing method;   one or more reagents for staining one or more cellular constituents to be stimulated for transposition with respect to cell membranes; and   a reagent for staining cell nuclei.   
     
     
         11 . The kit of  claim 10 , wherein the one or more constituents includes antibodies against E-cadherin. 
     
     
         12 . The kit of  claim 10 , wherein the one or more constituents includes antibodies against N-cadherin. 
     
     
         13 . The kit of  claim 10 , wherein the one or more constituents includes an antibody against VE-cadherin. 
     
     
         14 . The kit of  claim 10 , wherein the one or more constituents include pan-cadherin antibodies. 
     
     
         15 . The kit of  claim 10 , wherein the one or more constituents include antibodies against Protein Kinase Cα. 
     
     
         16 . The kit of  claim 10 , wherein the membrane activation image processing method includes:
 finding shapes of structures in cells in the image by a process adapted for the shapes;   finding contours of the structures based on the shapes; and,   generating a mask of the contours.   
     
     
         17 . A kit for visualization of lipid droplets in cells, comprising:
 a program product storing a program for a fat cell image processing method;   one or more reagents for staining lipid droplets; and   a reagent for staining cell nuclei.   
     
     
         18 . The kit of  claim 17 , wherein the one or more reagents includes a lipid stain constituted of 1 μg/ml 4,4-Difluoro-1,3,5,7,8-pentamethyl-4-bora-3a,4a-diaza-s-indacene. 
     
     
         19 . The kit of  claim 15 , wherein the lipid droplet image processing method includes:
 generating shapes of lipid droplets in cells in the original image by at least a one function adapted for finding rounded shapes in an image;   generating markers associated with the lipid droplets;   generating a mask of lipid droplet outlines in response to the shapes and the markers; and   measuring structures of lipid droplets in the original image with the mask.   
     
     
         20 . The kit of claim  21 , wherein generating shapes of lipid droplets includes generating shapes of small lipid droplets by a first function and generating shapes of large lipid droplets by a second function and generating an aggregate image of the shapes by the union of results produced by the first and second functions.