Cell counting
Systems and methods for classifying blood cells in a blood sample are disclosed. A series of frames of the blood sample as it flows through a field of view of an image capture device are captured and analysed. Advantageously, the disclosed systems and methods combine the availability of morphological cell data with the convenience of a flow-through arrangement. The classification results can be used for estimating cell counts in a blood sample.
1. A method of estimating a cell count in a blood sample, the method comprising
capturing a sequence of frames of the sample with an image capture device as the sample flows through a field of view of the image capture device;
identifying cells in each frame;
selecting a plurality of frames of the sequence of frames based on an estimate of cell velocity in one or more frames, wherein each frame is selected based on an estimate of the number of frames needed for all cells identified in the previous selected frame to leave the field of view, and determining a frame cell count of identified cells in each selected frame; and
combining the determined frame cell counts to compute an estimated cell count.
2. The method as claimed in claim 1 , wherein combining the frame cell counts and computing an estimated cell count includes fitting a distribution function to the determined frame cell counts and computing the estimated cell count based on the fitted distribution.
3. The method as claimed in claim 2 , wherein the distribution function is a Gamma distribution over frame cell counts.
4. The method as claimed in claim 2 , wherein combining the determined frame cell counts includes selecting a subset of the frame cell counts to combine, the subset being selected based on a combination of position of the respective frames in the sequence and a goodness of fit measure of the fitting of the distribution function.
5. The method as claimed in claim 1 , wherein combining the frame cell counts and computing an estimated cell counts includes determining a mean or median value of the frame cell counts.
6. The method as claimed in claim 1 , the method comprising computing a count per volume based on the estimated cell count and a flow volume associated with the field of view.
7. The method as claimed in claim 6 , the method comprising detecting an obstructed area in the field of view in which there is a flow obstruction and determining the flow volume by correcting an unobstructed volume associated with the field for a volume associated with the obstructed area.
8. The method as claimed 7 , wherein detecting an obstructed area includes partitioning the field of view into candidate areas and marking a candidate area as obstructed if less than a threshold amount of cells have been identified over the sequence of frames in that candidate area.
9. A system for estimating a cell count in a blood sample, the system comprising an image capture device having a field of view and an image processor, wherein the image processor is configured to:
capture a sequence of frames of the sample with the image capture device as the sample flows through the field of view of the image capture device;
identify cells in each frame;
select a plurality of frames of the sequence of frames based on an estimate of cell velocity in one or more frames, wherein each frame is selected based on an estimate of the number of frames needed for all cells identified in the previous selected frame to leave the field of view, and determine a frame cell count of identified cells in each selected frame; and
combine the determined frame cell counts to compute an estimated cell count in a volume corresponding to the field of view.
10. The system as claimed in claim 9 , wherein combining the frame cell counts and computing an estimated cell count includes fitting a distribution function to the distribution of determined frame cell counts and computing the estimated cell count based on the fitted distribution.
11. The system as claimed in claim 10 , wherein the distribution function is a Gamma distribution over frame cell counts.
12. The system as claimed in claim 10 , wherein combining the determined frame cell counts includes selecting a subset of the frame cell counts to combine, the subset being selected based on a combination of position of the respective frames in the sequence and a goodness of fit measure of the fitting of the distribution function.
13. The system as claimed in claim 9 , wherein combining the frame cell counts and computing an estimated cell counts includes determining a mean or median value of the frame cell counts.
14. The A system as claimed in claim 9 , wherein the image processor is configured to compute a count per volume based on the estimated cell count and a flow volume associated with the field of view.
15. The system as claimed in claim 14 , wherein the image processor is configured to detect an obstructed area in the field of view in which there is a flow obstruction determine the flow volume by correcting an unobstructed volume associated with the field for a volume associated with the obstructed area.
16. The system as claimed in claim 15 , wherein detecting an obstructed area includes partitioning the field of view into candidate areas and marking a candidate area as obstructed if less than a threshold amount of cells have been identified over the sequence of frames in that candidate area.
17. A system for estimating a cell count in a blood sample, the system comprising:
a processor and a non-transitory memory operably coupled to the processor; and
coded instructions which, when executed by the processor, implement the method as claimed in claim 1 .