Method for moving cell detection from temporal image sequence model estimation

Abstract

A computerized robust cell kinetic recognition method for moving cell detection from temporal image sequence receives an image sequence containing a current image. A dynamic spatial-temporal reference generation is performed to generate dynamic reference image output. A reference based object segmentation is performed to generate initial object segmentation output. An object matching and detection refinement is performed to generate kinetic recognition results output. The dynamic spatial-temporal reference generation step performs frame look ahead and the reference images contain a reference intensity image and at least one reference variation image.

1 . A computerized robust cell kinetic recognition method for moving cell detection from temporal image sequence comprising the steps of:
 a) Inputting an image sequence containing a current image;   b) Performing dynamic spatial-temporal reference generation using the image sequence having dynamic reference image output;   c) Performing reference based object segmentation having initial object segmentation output.   
     
     
         2 . The robust cell kinetic recognition method of  claim 1  further comprises a previous frame results storage and performing object matching and detection refinement using the initial object segmentation and the previous frame results having kinetic recognition results output. 
     
     
         3 . The robust cell kinetic recognition method of  claim 1  wherein the dynamic spatial temporal reference generation step performing frame look ahead. 
     
     
         4 . The robust cell kinetic recognition method of  claim 1  wherein the reference based object segmentation method subtracting the dynamic reference image from the current image. 
     
     
         5 . The robust cell kinetic recognition method of  claim 1  wherein the dynamic spatial-temporal reference generation method comprising the steps of:
 a) Inputting running interval image sequence; 
 b) Performing pixel statistics creation using the running interval image sequence having pixel statistics output; 
 c) Performing background time points detection using the running interval image sequence and the pixel statistics having background set output; 
 d) Performing reference image generation using the current image and the background set having reference intensity image output. 
 
     
     
         6 . The dynamic spatial-temporal reference generation method of  claim 5  further comprising the steps of:
 a) Performing at least one spatial-temporal variation enhancement using the current image having at least one variation image output; 
 b) Performing reference image generation using the at least one variation image having at least one reference variation image output.