IP Library Granted Patent US 12,211,610
Granted Patent B2
US 12,211,610 · App. 18/461,617 · Granted Jan 28, 2025

Systems and methods of automatically processing electronic images across regions

Inventors: Razik Yousfi (Brooklyn, NY); Peter Schueffler (Munich, DE); Thomas Fresneau (Oro Valley, AZ); Alexander Tsema (New York, NY)
Assignee: Paige.AI, Inc.
G16H30/40G06F18/2413G06N20/00G06T7/0012G16H10/60G16H30/20
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Quick Facts
Patent No.
US 12,211,610
App. No.
18/461,617
Granted
Jan 28, 2025
Kind
B2
Abstract

Systems and methods are disclosed for using an integrated computing platform to view and transfer digital pathology slides using artificial intelligence, the method including receiving at least one whole slide image in a cloud computing environment located in a first geographic region, the whole slide image depicting a medical sample associated with a patient, the patient being located in the first geographic region; storing the received whole slide image in a first encrypted bucket; applying artificial intelligence to perform a classification of the at least one whole slide image, the classification comprising steps to determine whether portions of the medical sample depicted in the whole slide image are healthy or diseased; based on the classification of the at least one whole slide image, generating metadata associated with the whole slide image; and storing the metadata in a second encrypted bucket.

Claims (48)

1. A method, the method comprising:

storing a whole slide image in a first encrypted bucket, the whole slide image being associated with a geographic region and depicting a medical sample associated with a patient;

determining, by artificial intelligence, whether portions of the medical sample are suspicious for disease;

generating metadata associated with the whole slide image based on whether portions of the medical sample are suspicious for disease; and

storing the metadata in a second encrypted bucket.

2. The method of claim 1 , further comprising:

receiving a request to transfer the whole slide image to a second geographic region; and

removing data from the whole slide image and/or the metadata based on one or more rules associated with the second geographic region to generate a modified whole slide image and modified metadata.

3. The method of claim 1 , further comprising:

receiving a request for the whole slide image from a client device; and

in response to determining that the client device is located in a first geographic region, providing the whole slide image and the metadata to the client device.

4. The method of claim 1 , further comprising:

in response to determining that a client device is not located in the first geographic region, processing the whole slide image to determine a second whole slide image.

5. The method of claim 1 , wherein storing the whole slide image further comprises performing automatic artificial-intelligence based ingestion of the whole slide image.

6. The method of claim 1 , wherein determining whether portions of the medical sample are suspicious for disease comprises determining a heatmap; and storing the heatmap in the second encrypted bucket.

7. The method of claim 1 , wherein generating metadata comprises determining a heatmap comprising a graphical prediction of a likelihood of disease in the medical sample.

8. The method of claim 1 , wherein determining whether portions of the medical sample are suspicious for disease is performed at least in part based on patient metadata.

9. A system for processing an electronic image 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:

storing a whole slide image in a first encrypted bucket, the whole slide image being associated with a geographic region and depicting a medical sample associated with a patient;

determining, by artificial intelligence, whether portions of the medical sample are suspicious for disease;

generating metadata associated with the whole slide image based on whether portions of the medical sample are suspicious for disease; and

storing the metadata in a second encrypted bucket.

10. The system of claim 9 , the operations further comprising:

receiving a request to transfer the whole slide image to a second geographic region; and

removing data from at least one of the whole slide image and the metadata based on rules associated with the second geographic region to generate a modified whole slide image and modified metadata.

11. The system of claim 9 , the operations further comprising:

determining whether a client device is located in a first geographic region; and in response to determining that the client device is located in the first geographic region, providing the whole slide image and the metadata to the client device.

12. The system of claim 9 , the operations further comprising:

determining whether a client device is located in the first geographic region; and

in response to determining that the client device is not located in the first geographic region, processing the whole slide image to determine a second whole slide image, and processing the metadata to produce modified metadata.

13. The system of claim 9 , wherein storing the whole slide image comprises performing automatic artificial-intelligence based ingestion of the whole slide image.

14. The system of claim 9 , further comprising: wherein determining whether portions of the medical sample are suspicious for disease comprises determining a heatmap; and storing the heatmap in the second encrypted bucket.

15. The system of claim 9 , wherein determining whether portions of the medical sample are suspicious for disease is performed at least in part based on patient metadata.

16. A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the processor to perform operations comprising:

storing a whole slide image in a first encrypted bucket, the whole slide image being associated with a geographic region and depicting a medical sample associated with a patient;

determining, by artificial intelligence, whether portions of the medical sample are suspicious for disease;

generating metadata associated with the whole slide image based on whether portions of the medical sample are suspicious for disease; and

storing the metadata in a second encrypted bucket.

17. The non-transitory computer-readable medium of claim 16 , the operations further comprising receiving a request to transfer the whole slide image to a second geographic region; and removing data from at least one of the whole slide image and the metadata based on one or more rules associated with the second geographic region to generate a modified whole slide image and modified metadata.

18. The non-transitory computer-readable medium of claim 17 , the operations further comprising: providing the modified whole slide image and modified metadata for transfer to the second geographic region.

19. The non-transitory computer-readable medium of claim 16 , the operations further comprising:

determining whether a client device is located in a first geographic region; and

in response to determining that the client device is located in the first geographic region, providing the whole slide image and the metadata to the client device.

20. The non-transitory computer-readable medium of claim 16 , the operations further comprising:

determining whether a client device is located in the first geographic region; and

in response to determining that the client device is not located in the first geographic region, processing the whole slide image to determine a second whole slide image, and processing the metadata to produce modified metadata, the processing of the whole slide image and the processing of the metadata being based upon one or more rules associated with the first geographic region.

Assignments (3)
RELEASE OF SECURITY INTEREST Recorded May 14, 2026
From: ARES CAPITAL CORPORATION, AS COLLATERAL AGENT
To: PAIGE.AI, INC.
Reel/Frame 075589/0752 →
SECURITY INTEREST Recorded Oct 21, 2025
From: PAIGE.AI, INC.
To: ARES CAPITAL CORPORATION, AS COLLATERAL AGENT
Reel/Frame 073216/0876 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 22, 2023
From: YOUSFI, RAZIK; SCHUEFFLER, PETER; FRESNEAU, THOMAS; TSEMA, ALEXANDER
To: PAIGE.AI, INC.
Reel/Frame 064997/0883 →
Continuity (5)
Continuation 17805992 · Jun 8, 2022
Continuation 17530372 · Nov 18, 2021
Continuation 17200563 · Mar 12, 2021
Provisional Application 62989095 · Mar 13, 2020
Related Publication 20230410987A1 · Dec 21, 2023
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