Counting impacts on a target (Traces of heavy ions beam) with the help of kmeans clustering.

When studying effect of ionizing radiation (heavy ions with high LET) on cells, the fluence (particules/cm²) of the particles beam must be known. Detectors in the GANIL (Caen, France) particles accelerator can estimate the fluence. However, when irradiating cells, radiobiologists (CEA CIRIL) need to localize the impacts of the ions and to count the number of impact per cell.

The application TRACES (scripts for the aphelion application) was developped: It was capable of recording and saving images from a camera, segmenting and counting traces: 

The application was designed to analyse images as the following:

raw image of traces

Counting impacts  in a python notebook:

Contrary to the TRACES application, the following jupyter notebook can't capture images (It should be possible to do it in a python script with the cv2 module) but it can perform some automatic classification.

Distinguishing traces resulting from one or several impacts is a classification issue which can be explored with unsupervised classifier such k-means clustering: