Systems and methods to process electronic images to produce a tissue map visualization

1. A computer-implemented method for analyzing an image of a slide corresponding to a specimen, the method comprising:

receiving at least one digitized image of a pathology specimen;

determining, using the digitized image at an artificial intelligence (AI) system, at least one salient feature, the at least one salient feature comprising a biomarker, cancer, cancer grade, parasite, toxicity, inflammation, and/or cancer sub-type;

determining, at the AI system, a salient region overlay for the digitized image, wherein the AI system indicates a value for each pixel;

representing the salient region overlay by a set of super-pixels associated with a score, the score being associated with the at least one salient feature being present or absent;

suppressing, based on the value for each pixel, one or more non-salient regions of the digitized image; and

converting the salient region overlay into a tissue map.

2. The computer-implemented method of claim 1 , further comprising normalizing the salient region overlay to obtain a variable.

3. The computer-implemented method of claim 2 , wherein the salient region overlay is represented by one or more of:

a heatmap indicating a score or a probability for each pixel of a salient feature being present or absent;

a binary segmentation of the digitized image indicating if each pixel has or does not have the salient feature present; and

a semantic segmentation of the digitized image indicating a score or probability for each pixel.

4. The computer-implemented method of claim 1 , wherein detecting a salient feature uses image processing techniques, AI, or machine learning on the digitized image to produce a tissue visualization.

5. The computer-implemented method of claim 1 , wherein the digitized image comprises related case information, patient information and information from a clinical system.

6. The computer-implemented method of claim 1 , further comprising alerting a user when the salient region overlay is available.

7. The computer-implemented method of claim 1 , wherein the salient region overlay is resized to a same size as the digitized image.

8. The computer-implemented method of claim 1 , further comprising developing a pipeline to archive a plurality of processed images or prospective patient data.

9. The A system for analyzing an image of a slide corresponding to a specimen, 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 digitized image of a pathology specimen;

determining, using the digitized image at an artificial intelligence (AI) system, at least one salient feature, the at least one salient feature comprising a biomarker, cancer, cancer grade, parasite, toxicity, inflammation, and/or cancer sub-type;

determining, at the AI system, a salient region overlay for the digitized image, wherein the AI system indicates a value for each pixel;

representing the salient region overlay by a set of super-pixels associated with a score, the score being associated with the at least one salient feature being present or absent;

suppressing, based on the value for each pixel, one or more non-salient regions of the digitized image; and

converting the salient region overlay into a tissue map.

10. The system of claim 9 , further comprising normalizing the salient region overlay to obtain a variable.

11. The system of claim 10 , wherein the salient region overlay is represented by one or more of:

a heatmap indicating a score or a probability for each pixel of a salient feature being present or absent;

a binary segmentation of the digitized image indicating if each pixel has or does not have the salient feature present; and

a semantic segmentation of the digitized image indicating a score or probability for each pixel.

12. The system of claim 9 , wherein detecting a salient feature uses image processing techniques, AI, or machine learning on the digitized image to produce a tissue visualization.

13. The system of claim 9 , wherein the digitized image comprises related case information, patient information, and information from a clinical system.

14. The system of claim 9 , further comprising alerting a user when the salient region overlay is available.

15. The system of claim 9 , wherein the salient region overlay is resized to a same size as the digitized image.

16. The system of claim 9 , further comprising developing a pipeline to archive a plurality of processed images or prospective patient data.

17. A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the processor to perform a method for analyzing an image of a slide corresponding to a specimen, the method comprising:

receiving at least one digitized image of a pathology specimen;

determining, using the digitized image at an artificial intelligence (AI) system, at least one salient feature, the at least one salient feature comprising a biomarker, cancer, cancer grade, parasite, toxicity, inflammation, and/or cancer sub-type;

determining, at the AI system, a salient region overlay for the digitized image, wherein the AI system indicates a value for each pixel;

representing the salient region overlay by a set of super-pixels associated with a score, the score being associated with the at least one salient feature being present or absent;

suppressing, based on the value for each pixel, one or more non-salient regions of the digitized image; and

converting the salient region overlay into a tissue map.