US 10991097

US Patent 10991097, titled "Artificial intelligence segmentation of tissue images," was issued to Tempus AI Inc. The patent describes methods and systems for analyzing digital medical images, particularly histological slides of cancerous tissue, using artificial intelligence.

Here is a summary of the patent details:

• Title: Artificial intelligence segmentation of tissue images
• Assignee: Tempus AI Inc (current assignee as of February 9, 2024, via change of name from Tempus Labs Inc)
• Inventors: Stephen Yip, Irvin Ho, Lingdao Sha, Boleslaw Osinski
• Filing Date: December 31, 2019
• Issue Date: April 27, 2021
• Abstract: "Techniques for generating an overlay map on a digital medical image of a slide are provided, and include cell detection and tissue classification processes. Techniques include receiving a medical image, separating the image into tiles, and performing tile classifications and tissue classifications based on a multi-tile analysis. Techniques additionally include identifying cell objects in the image, separating the image into and displaying polygons identifying the cell objects and cell classifications. Generated displays may be overlays over the initial digital image."

Independent Claims Overview:

Independent Claim 1:
This claim describes a computer-implemented method for creating an overlay map on a digital image of a slide. The method involves receiving a digital image, dividing it into multiple tiles, and then identifying the most prevalent tissue class within each tile using an analysis that considers multiple tiles.

Independent Claim 11:
This claim describes a computer-implemented method for classifying tissue in a digital image of a slide. It involves receiving the digital image, generating a digital overlay drawing specifically for a tissue region within that image, and then displaying tiles over this tissue region. The method visually identifies the predicted content of each tile to create a classification map of the digital image.

Independent Claim 14:
This claim describes a computer-implemented method for detecting cells in a digital image of a slide. The method receives the digital image, identifies specific cell objects within it, generates a digital overlay drawing for the image, and then displays a polygon outline around each of the identified cell objects in this overlay.

Independent Claim 17:
This claim describes a computer-implemented method for classifying tissue in a digital image of a slide that combines both tile and cell-level analysis. It involves receiving the digital image, segmenting it into tiles, and predicting a class for each tile. Simultaneously, it identifies multiple cell objects in the image and predicts a class for each cell object. Crucially, for any tile that corresponds to an identified cell object, the method assigns the predicted class of that specific cell object to the tile, overriding the tile's initial predicted class.

Independent Claim 27:
This claim describes a system that performs the methods outlined in independent claim 1. It comprises a processor and a computer-readable memory storing instructions. When executed by the processor, these instructions cause the system to receive a digital image, divide it into tiles, and identify the majority tissue class within each tile based on a multi-tile analysis.

Independent Claim 30:
This claim describes a system that performs the methods outlined in independent claim 11. It includes a processor and a computer-readable memory storing instructions. When executed, these instructions enable the system to receive a digital image, generate an overlay drawing of a tissue region, and display tiles over that region, visually identifying the predicted content of each tile to generate a classification map.

Independent Claim 31:
This claim describes a system that performs the methods outlined in independent claim 14. It comprises a processor and a computer-readable memory storing instructions. When executed, these instructions cause the system to receive a digital image, identify cell objects, generate a digital overlay drawing, and display polygons outlining each identified cell object.

Independent Claim 32:
This claim describes a system that performs the methods outlined in independent claim 17. It includes a processor and a computer-readable memory storing instructions. When executed, these instructions enable the system to receive a digital image, segment it into tiles, determine a predicted class for each tile, identify cell objects, determine a predicted class for each cell object, and for corresponding tiles and cell objects, assign the cell object's predicted class to the tile.

Legal Status and Litigation:

As of April 26, 2026, the patent US10991097B2 is listed as "Active" with an anticipated expiration date of December 31, 2039.

There are several litigation activities noted:

• A PTAB case, IPR2026-00185, was filed and is currently pending.
• The first worldwide family litigation was filed.
• US cases were filed in the California Northern District Court (cases 3:25-cv-06622 and 5:25-cv-06622).
• A US case was filed in the California Southern District Court (case 3:25-cv-00621).

There is no mention of specific CAFC 2026 dockets in the provided patent information. The pending IPR case would typically be heard by the PTAB (Patent Trial and Appeal Board), and the district court cases are at the district level. Appeals from these bodies would go to the CAFC, but no specific CAFC dockets for 2026 are explicitly listed as active for this patent in the provided text.