RBC, easy as 1, 2, 3

After monitoring cell thickness (during mitosis) and cell movement, the number and position of RBCs from a blood sample were analyzed in a systematic manner with the 3D Cell Explorer and its software STEVE. We developed a little script (that will be integrated on our cloud soon) which allows for fast and simple segmentation of cell data.

The process is the following:

  1. Open a .vol file on STEVE (in this case Alvaro’s blood data were reused to this aim)
  2. Filter out background noise
  3. Apply morphological filters to the image in order to isolate the RBCs
  4. Get the number and exact position of the cells in your field of view

The whole process is showed on the figure below.

This simple method combined with the 3D Cell Explorer could lead to the automatic diagnosis of many common blood pathologies. Indeed, a high RBCs count is an indicator of liver or kidney disease, while a low count might suggest anemia. 

If you are curious about other blood analysis executed with the 3D Cell Explorer, check out our malaria blog post and watch our webinars if you want to have more insight into our technology.

 

final_image2

Figure. On the top is represented the RI map of the acquisition (left panel), the 3D reconstruction (right panel) and the staining panel (center) of the RBCs. On the bottom are represented the different image processing steps.