BACTERIA CLASSIFICATION

20210040530

16/536613

August 09, 2019

A method, a computer program product, and a computer system for classifying bacteria. The method comprises extracting a morphology signature corresponding to one or more bacteria and extracting a motility signature corresponding to the one or more bacteria. The method further comprises merging the morphology signature and the motility signature into a merged vector signature and classifying the one or more bacteria based on the merged vector signature.

1. A computer-implemented method for classifying bacteria, the method comprising: extracting a morphology signature corresponding to one or more bacteria; extracting a motility signature corresponding to the one or more bacteria; merging the morphology signature and the motility signature into a merged vector signature; and classifying the one or more bacteria based on the merged vector signature.

2. The method of claim 1, wherein extracting the morphology signature is based on comparing a morphology of the one or more bacteria to a model correlating bacteria morphology with bacteria type.

3. The method of claim 2, wherein the model correlating bacteria morphology with bacteria type includes features selected from a group comprising cell size, cell shape, cell length, cell diameter, cell volume, and gram stain type.

4. The method of claim 1, wherein extracting the motility signature is based on comparing a motility of the one or more bacteria to a model correlating bacteria motility with bacteria type.

5. The method of claim 4, wherein the model correlating bacteria motility with bacteria type includes features selected from a group comprising a run length, an average run length, a run velocity, an average run velocity, a tumble length, an average tumble length, a tumble velocity, an average tumble velocity, and a tumble interval.

6. The method of claim 1, wherein the model correlating bacteria motility with bacteria type further includes the feature replication rate.

7. The method of claim 1, wherein the morphology signature, the motility signature, and the merged vector signature are generated via artificial intelligence algorithms.

8. A computer program product for classifying bacteria, the computer program product comprising: one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media capable of performing a method, the method comprising: extracting a morphology signature corresponding to one or more bacteria; extracting a motility signature corresponding to the one or more bacteria; merging the morphology signature and the motility signature into a merged vector signature; and classifying the one or more bacteria based on the merged vector signature.

9. The computer program product of claim 8, wherein extracting the morphology signature is based on comparing a morphology of the one or more bacteria to a model correlating bacteria morphology with bacteria type.

10. The computer program product of claim 9, wherein the model correlating bacteria morphology with bacteria type includes features selected from a group comprising cell size, cell shape, cell length, cell diameter, cell volume, and gram stain type.

11. The computer program product of claim 8, wherein extracting the motility signature is based on comparing a motility of the one or more bacteria to a model correlating bacteria motility with bacteria type.

12. The computer program product of claim 11, wherein the model correlating bacteria motility with bacteria type includes features selected from a group comprising a run length, an average run length, a run velocity, an average run velocity, a tumble length, an average tumble length, a tumble velocity, an average tumble velocity, and a tumble interval.

13. The computer program product of claim 8, wherein the model correlating bacteria motility with bacteria type further includes the feature replication rate.

14. The computer program product of claim 8, wherein the morphology signature, the motility signature, and the merged vector signature are generated via artificial intelligence algorithms.

15. A computer system for classifying bacteria, the computer system comprising: one or more computer processors, one or more computer-readable storage media, and program instructions stored on the one or more of the computer-readable storage media for execution by at least one of the one or more processors capable of performing a method, the method comprising: extracting a morphology signature corresponding to one or more bacteria; extracting a motility signature corresponding to the one or more bacteria; merging the morphology signature and the motility signature into a merged vector signature; and classifying the one or more bacteria based on the merged vector signature.

16. The computer system of claim 15, wherein extracting the morphology signature is based on comparing a morphology of the one or more bacteria to a model correlating bacteria morphology with bacteria type.

17. The computer system of claim 16, wherein the model correlating bacteria morphology with bacteria type includes features selected from a group comprising cell size, cell shape, cell length, cell diameter, cell volume, and gram stain type.

18. The computer system of claim 15, wherein extracting the motility signature is based on comparing a motility of the one or more bacteria to a model correlating bacteria motility with bacteria type.

19. The computer system of claim 18, wherein the model correlating bacteria motility with bacteria type includes features selected from a group comprising a run length, an average run length, a run velocity, an average run velocity, a tumble length, an average tumble length, a tumble velocity, an average tumble velocity, and a tumble interval.

20. The computer system of claim 15, wherein the model correlating bacteria motility with bacteria type further includes the feature replication rate.

12; 16; 06

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