Systems and methods for artificial intelligence powered molecular workflow verifying slide and block quality for testing

1. A computer-implemented method of selecting a formalin fixed paraffin embedded (FFPE) tissue block in a genomic assay, the method comprising:

receiving at least one collection of digital images, the collection being associated with a tissue block and corresponding to an instance, at a digital storage device;

applying a machine learning model to the collection, the machine learning model determining whether the collection contains an amount of a tumor tissue beyond a threshold;

determining a location of the tumor tissue; and

outputting a confirmation indicating that an adequate amount of the tumor tissue exists within the FFPE tissue block.

2. The computer-implemented method of claim 1 , further comprising:

partitioning each of the collection into a collection of tiles associated with one or the collection of digital images;

detecting and/or segmenting a tissue region from a background of each digital image to create a tissue mask; and

and removing all tiles in the collection of tiles that comprise the background.

3. The computer-implemented method of claim 2 , wherein detecting and/or segmenting comprises using thresholding-based methods and running a connected components algorithm.

4. The computer-implemented method of claim 2 , wherein detecting and/or segmenting comprises using one or more segmentation algorithms.

5. The computer-implemented method of claim 1 , further comprising:

identifying a tissue block with an adequate amount of tissue tumor for subsequent testing; and

indicating to a user that the tissue block has at least one additional slide to prepare for testing.

6. The computer-implemented method of claim 1 , further comprising:

determining that the amount of the tumor tissue is sufficiently low; and indicating to a user to prepare a new block for testing.

7. The computer-implemented method of claim 1 , further comprising:

outputting a binary confirmation indicating the FFPE tissue block contains enough tumor tissue to test.

8. The computer-implemented method of claim 1 , further comprising: outputting a binary image indicating where the tissue tumor is located.

9. The computer-implemented method of claim 1 , further comprising: receiving a synoptic annotation comprising one or more label for each digital image.

10. The computer-implemented method of claim 9 , wherein the one or more label is at one or more of a pixel-level label, a tile level label, a slide-level label, and/or a part specimen-level label.

11. A system for using a machine learning model to select a formalin fixed paraffin embedded (FFPE) tissue block in a genomic assay, the system comprising:

at least one memory storing instructions; and

at least one processor configured to execute the instructions to perform operations comprising:

receiving at least one collection of digital images, the collection being associated with a tissue block and corresponding to an instance, at a digital storage device;

applying a machine learning model to the collection, the machine learning model determining whether the collection contains an amount of a tumor tissue beyond a threshold;

determining a location of the tumor tissue; and

outputting a confirmation indicating that an adequate amount of the tumor tissue exists within the FFPE tissue block.

12. The system of claim 11 , wherein the operations further comprise:

partitioning each of the collection into a collection of tiles associated with one or the collection of digital images;

detecting and/or segmenting a tissue region from a background of each digital image to create a tissue mask; and

and removing all tiles in the collection of tiles that comprise the background.

13. The system of claim 12 , wherein detecting and/or segmenting comprises using thresholding-based methods and running a connected components algorithm.

14. The system of claim 12 , wherein detecting and/or segmenting comprises using one or more segmentation algorithms.

15. The system of claim 11 , wherein the operations further comprise outputting a binary confirmation indicating the FFPE tissue block contains enough tumor tissue to test.

16. The system of claim 11 , wherein the operations further comprise outputting a binary image indicating where the tissue tumor is located.

17. A non-transitory computer-readable medium storing instructions that, when executed by a processor, perform a method of selecting a formalin fixed paraffin embedded (FFPE) tissue block in a genomic assay, the method comprising:

receiving at least one collection of digital images, the collection being associated with a tissue block and corresponding to an instance, at a digital storage device;

applying a machine learning model to the collection, the machine learning model determining whether the collection contains an amount of a tumor tissue beyond a threshold;

determining a location of the tumor tissue; and

outputting a confirmation indicating that an adequate amount of the tumor tissue exists within the FFPE tissue block.

18. The computer-readable medium of claim 17 , wherein the method further comprises:

partitioning each of the collection into a collection of tiles associated with one or the collection of digital images;

detecting and/or segmenting a tissue region from a background of each digital image to create a tissue mask; and

and removing all tiles in the collection of tiles that comprise the background.

19. The computer-readable medium of claim 18 , wherein detecting and/or segmenting comprises using thresholding-based methods and running a connected components algorithm.

20. The computer-readable medium of claim 18 , wherein detecting and/or segmenting comprises using one or more segmentation algorithms.