Apparatus and method for analyzing a bodily sample

Patent metadata

Field	Value
Publication number	US-12005443-B2
Application number	US-202017064193-A
Country	US
Kind code	B2
Filing date	Oct 6, 2020
Priority date	Dec 29, 2010
Publication date	Jun 11, 2024
Grant date	Jun 11, 2024

Abstract

Apparatus and methods are described including successively acquiring a plurality of microscopic images of a portion of a blood sample, and tracking motion of pixels within the successively acquired microscopic images. Trypomastigote parasite candidates within the blood sample are identified, by identifying pixel motion that is typical of trypomastigote parasites. It is determined that the blood sample is infected with trypomastigote parasites, at least partially in response thereto. An output is generated indicating that that the blood sample is infected with trypomastigote parasites. Other applications are also described.

First claim

The invention claimed is:

1. A method comprising:
successively acquiring a plurality of microscopic images of a portion of a blood sample;
tracking motion of pixels within the successively acquired microscopic images;
identifying trypomastigote parasite candidates within the blood sample, by identifying pixel motion that is typical of trypomastigote parasites;
determining that the blood sample is infected with trypomastigote parasites, at least partially in response thereto; and
generating an output indicating that that the blood sample is infected with trypomastigote parasites.

2. The method according to claim 1 , wherein identifying trypomastigote parasite candidates within the blood sample further comprises identifying entities having a worm-like shape.

3. The method according to claim 1 , wherein identifying pixel motion that is typical of trypomastigote parasites comprises identifying entities that undergo a twirling motion.

4. The method according to claim 1 , wherein identifying pixel motion that is typical of trypomastigote parasites comprises identifying entities that undergo a spinning motion.

5. The method according to claim 1 , wherein successively acquiring the plurality of microscopic images of the portion of the blood sample comprises successively acquiring a plurality of fluorescent microscopic images of a portion of a blood sample, and wherein identifying pixel motion that is typical of trypomastigote parasites comprises identifying motion of fluorescent particles that is typical of trypomastigote parasites.

6. The method according to claim 1 , wherein identifying trypomastigote parasite candidates within the blood sample comprises identifying trypomastigote parasite candidates using a multi-frame candidate construction module in which the candidates are assessed for coherency over at least some of the plurality of the microscopic images.

7. The method according to claim 1 , wherein generating the output indicating that that the blood sample is infected with trypomastigote parasites comprises generating an image in which the trypomastigote parasites are visible.

8. The method according to claim 1 , wherein generating the output indicating that that the blood sample is infected with trypomastigote parasites comprises generating an output indicating that a subject from whom the blood sample was taken is suffering from human African trypanosomiasis.

9. Apparatus comprising:
a microscope; and
a computer processor configured to:
drive the microscope to successively acquiring a plurality of microscopic images of a portion of a blood sample;
track motion of pixels within the successively acquired microscopic images;
identify trypomastigote parasite candidates within the blood sample, by identifying pixel motion that is typical of trypomastigote parasites;
determine that the blood sample is infected with trypomastigote parasites, at least partially in response thereto; and
generate an output indicating that that the blood sample is infected with trypomastigote parasites.

10. The apparatus according to claim 9 , wherein the computer processor is configured to identify trypomastigote parasite candidates within the blood sample by identifying entities having a worm-like shape.

11. The apparatus according to claim 9 , wherein the computer processor is configured to identify pixel motion that is typical of trypomastigote parasites by identifying entities that undergo a twirling motion.

12. The apparatus according to claim 9 , wherein the computer processor is configured to identify pixel motion that is typical of trypomastigote parasites by identifying entities that undergo a spinning motion.

13. The apparatus according to claim 9 , wherein the computer processor is configured to drive the microscope to successively acquire a plurality of fluorescent microscopic images of a portion of the blood sample, and wherein the computer processor is configured to identify pixel motion that is typical of trypomastigote parasites by identifying motion of fluorescent particles that is typical of trypomastigote parasites.

14. The apparatus according to claim 9 , wherein the computer processor is configured to identify trypomastigote parasite candidates within the blood sample by identifying trypomastigote parasite candidates using a multi-frame candidate construction module in which the candidates are assessed for coherency over at least some of the plurality of the microscopic images.

15. The apparatus according to claim 9 , wherein the computer processor is configured to generate the output indicating that that the blood sample is infected with trypomastigote parasites by generating an image in which the trypomastigote parasites are visible.

16. The apparatus according to claim 9 , wherein the computer processor is configured to generate the output indicating that that the blood sample is infected with trypomastigote parasites by generating an output indicating that a subject from whom the blood sample was taken is suffering from human African trypanosomiasis.

Assignees

• S D Sight Diagnostics Ltd

Inventors

• Bachelet Ido
• Pollak Joseph Joel
• Levner Daniel
• Bilu Yonatan
• Yorav-Raphael Noam

Classifications

• G01N2021/5957

  using an image detector type detector, e.g. CCD · CPC title

• G01N2015/016

  White blood cells · CPC title

• G01N15/1433

  using image recognition · CPC title

• G06V2201/04

  Recognition of patterns in DNA microarrays · CPC title

• G06V2201/03

  Recognition of patterns in medical or anatomical images · CPC title