High accuracy 5-part differential with digital holographic microscopy and untouched leukocytes from peripheral blood

1. A method for marker-free detection of a cell type of at least one cell in a medium, comprising:

flowing a medium comprising at least one cell into a microfluidic device,

obtaining an image of the at least one cell in the microfluidic device by a digital holographic microscopic device, wherein the image is obtained with a depth of field of less than 6 μm, and

determining the cell type of the at least one cell.

2. The method of claim 1 , wherein the image is obtained with a lateral resolution of less than 0.6 μm.

3. The method of claim 1 , wherein the marker-free detection is carried out while flowing the medium comprising the at least one cell through the microfluidic device.

4. The method of claim 3 , wherein the flow in the microfluidic device is at least laminar in a region wherein the image of the at least one cell is obtained.

5. The method of claim 4 , wherein the microfluidic device comprises a microchannel in the region wherein the image of the at least one cell is obtained in which the laminar flow is produced by at least one sheath flow.

6. The method of claim 5 , wherein surfaces of the microchannel perpendicular to a wavefront of a reference or detection beam of the digital holographic microscopic device are essentially planar.

7. The method of claim 1 , wherein a field of view of the digital holographic microscopic device is at most 1.0 times a width of the microfluidic device in a region wherein the image of the at least one cell is obtained.

8. The method of claim 1 , wherein the at least one cell is a blood cell.

9. The method of claim 8 , wherein the blood cell is a white blood cell.

10. The method of claim 1 , wherein determining of the cell type of the at least one cell is carried out using a deep learning network.

11. The method of claim 1 , wherein a reference beam and a detection beam of the digital holographic microscopic device are off axis.

12. The method of claim 1 , wherein the determining the cell type of the at least one cell comprises determining the cell type of the at least one cell to be one selected from the group of a neutrophil, eosinophil, and basophil.

13. A device for marker-free detection of a cell type of at least one cell in a medium, comprising:

a digital holographic microscopic device with a depth of field of less than 6 μm;

a microfluidic device; and

a detection system configured to determine the cell type of the at least one cell.

14. The device of claim 13 , wherein the digital holographic microscopic device has a lateral resolution of less than 0.6 μm.

15. The device of claim 13 , wherein the microfluidic device comprises a microchannel in a region wherein the image of the at least one cell is obtained, wherein the microfluidic device further comprises means to produce a laminar flow in the microchannel.

16. The device of claim 13 , wherein the device for marker-free detection comprises a deep learning network.

17. A method for marker-free detection of a cell type of at least one cell in a medium, comprising:

flowing a medium comprising at least one cell into a microfluidic device;

obtaining an image of the at least one cell in the microfluidic device by a digital holographic microscopic device; and

determining the cell type of the at least one cell to be one selected from the group of a neutrophil, eosinophil, and basophil;

wherein the at least one cell is unfixed and unstained,

wherein the image is obtained with a depth of field of less than 6 μm.

18. The method of claim 17 , wherein the image is obtained with a lateral resolution of less than 0.6 μm.

19. The method of claim 17 , wherein a field of view of the digital holographic microscopic device is at most 1.0 times a width of the microfluidic device in a region wherein the image of the at least one cell is obtained.