IP Library Patent Application 18948792
Patent Application
App. No. 18/948,792

SYSTEMS AND METHODS FOR ARTIFICIAL INTELLIGENCE POWERED MOLECULAR WORKFLOW VERIFYING SLIDE AND BLOCK QUALITY FOR TESTING

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Quick Facts
Patent No.
US None
App. No.
18/948,792
Abstract

Systems and methods are disclosed for verifying slide and block quality for testing. The method may comprise receiving a collection of one or more digital images at a digital storage device. The collection may be associated with a tissue block and corresponding to an instance. The method may comprise applying a machine learning model to the collection to identify a presence or an absence of an attribute, determining an amount or a percentage of tissue with the attribute from a digital image in the collection that indicates the presence of the attribute, and outputting a quality score corresponding to the determined amount or percentage.

Claims (48)

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

receiving a collection of digital images, at a digital storage device;

applying a machine learning model to the collection, the machine learning model determining whether the collection contains a presence of an attribute of a tissue beyond a predetermined threshold;

determining a location of the tissue; and

outputting a confirmation indicating that an adequate presence of the 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 more of 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 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 presence of the 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 tissue to test.

8 . The computer-implemented method of claim 1 , further comprising: outputting a binary image indicating where the tissue 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 a collection of digital images, at a digital storage device;

applying a machine learning model to the collection, the machine learning model determining whether the collection contains a presence of an attribute of a tissue beyond a predetermined threshold;

determining a location of the tissue; and

outputting a confirmation indicating that an adequate presence of the 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 tissue to test.

16 . The system of claim 11 , wherein the operations further comprise outputting a binary image indicating where the tissue 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 a collection of digital images, at a digital storage device;

applying a machine learning model to the collection, the machine learning model determining whether the collection contains a presence of an attribute of a tissue beyond a predetermined threshold;

determining a location of the tissue; and

outputting a confirmation indicating that an adequate presence of the 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 more of 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.

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 Dec 17, 2024
From: RACITI, PATRICIA; KANAN, CHRISTOPHER; BOZKURT, ALICAN; DOGDAS, BELMA
To: PAIGE.AI, INC.
Reel/Frame 069608/0962 →