Cell finding

Identifying objects in an image is an area that offers a range of choices. The ideal outcome is to find objects of interest, such as the nuclei of cells, and reject everything else in the image. The more sophisticated an algorithm used, the better the result will be. The trade-off is that with increased processing the slower the scan becomes because of the time spent making calculations. On the other hand the user may not be too worried about false identification of objects or missing too many objects of interest, just wanting to process samples as quickly as possible with decent results. Therefore options exist to cover these situations. 



Why pre-process?
The result of pre-processing is to generate areas containing objects whose general features suggest they are what we are looking for. From this point more sophisticated analysis can be carried out (by the CHARM algorithm) on these areas to accurately calculate the loci of what we are after. Without pre-processing the CHARM algorithm has the entire image to work on and this will require time, leading to a slower scan. On the other hand, why not pre-process all the time? The answer is that when illumination conditions aren't ideal the thresholding technique can fail. Good contrast and uniform illumination is needed for basic thresholding to work, and when this isn't the case then other methods, like edge detection, perform better. If objects are being missed with pre-processing then it might be worth allowing more time for the scan and unchecking this option.

Pre-process images - If this is selected then after a snapped image is taken, thresholding is applied. This essentially separates out bright objects from the rest of the image. If 'simple threshold' is checked then the numerical value set by the user on the slider is used to determine which pixels to be treated as bright (and thus form part of an object) and which to be ignored. Unchecking this box hands control of threshold setting to the program which looks at the intensity information in each image to determine the level to set.
Minimum/Maximum cell diameter - We may know that the objects we are interested in tend to have a limited range of sizes. So to narrow down the objects found so far we can apply a size filter, based on minimum and maximum diameters, to retain only those which fall between the 2 limits specified.
Threshold - To know what threshold to set move to an area on the sample and take a camera snap. Now, moving the threshold slider will show what lies above and below the threshold limit.

Save cell data - It is usual that the user will want to save details of the objects found. The most obvious details are the co-ordinates of the stage needed to bring the object back into the field of view (at the cross-hairs). Other data is saved too, such as object size, average intensity, etc. However, this option may not always be needed, for example when simply the total number of objects in a region is all that is needed.
Show processing - At the expense of a small amount of time it is possible to show some steps in the object-finding procedure as the scan progresses. This may be an aid in judging whether pre-processing is performing adequately or not.

Simple object-finding can be carried out by identifying the centers of objects found through thresholding. For well defined and well spaced single objects this approach can be very successful. When, however, objects are touching or appear wrongly shaped then the loci assigned to them will be incorrect. Another method of analysis is needed.

Enable CHARM - An algorithm called CHARM (compact Hough and radial map) can be used. The essence of the technique is as follows. Edge detection is performed on the image, i.e. areas are identified where the intensity changes sharply (such as at the boundary of a cell). The assumption is then made that the center of an object of interest lies somewhere along a line perpendicular to this edge (just as the center of a circle lies on a line, a radius, which is perpendicular to an edge, a tangent, of the circle). Now, imagining all the edges forming the boundary of an object and all the lines perpendicular to these edges, it can be seen that they should all point in the same direction and cross at the object's center. This is how object centers are found. There are two marked advantages of this method over conventional thresholding. Firstly, absolute brightness of the object is not critical - all that matters is the degree of contrast between the object and the background. So dimly lit areas of the field are not such a problem. Secondly, the algorithm is robust against incomplete information. For example when two objects join, as in a cell doublet, and part of the boundary is missing, the radii which remain will still point correctly toward the cells' centers and indicate 2 points where 'radii crossing' is maximum.

So to get the best object-finding available, tick the 'Enable CHARM' box. If desired the 'Advanced' button brings up the options to set the CHARM parameters numerically or use the optimizer to visulaize the action of the CHARM algorithm based on selected settings.