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US-2018312803-A1 · Nov 1, 2018 · US
Machine-learned cell counting or cell confluence for a plurality of cell types
US12437396B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12437396-B2 |
| Application number | US-202217957042-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 30, 2022 |
| Priority date | Oct 1, 2021 |
| Publication date | Oct 7, 2025 |
| Grant date | Oct 7, 2025 |
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- Title
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Abstract
Official abstract text for this publication.
Various examples of the disclosure relate to techniques to count cells in a microscopy image and/or to determine a degree of confluence of the cells in the microscopy image. To that end, machine-learned algorithms are used.
First claim
Opening claim text (preview).
What is claimed is: 1. A computer-implemented method, comprising: acquiring a light-microscope image, which images a multiplicity of cells of a plurality of cell types, determining a plurality of density maps for the light-microscope image using a plurality of machine-learned processing paths of at least one machine-learned algorithm, wherein the plurality of processing paths are assigned to the plurality of cell types, wherein the plurality of density maps each encodes a probability for the presence or absence of cells of a corresponding cell type, and on the basis of the plurality of density maps and for each of the plurality of cell types: determining at least one of an estimation of a number or of a degree of confluence of the respective cells. 2. The computer-implemented method as claimed in claim 1 , further comprising: plausiblising the plurality of density maps by a spatially resolved comparison. 3. The computer-implemented method as claimed in claim 1 , wherein the plurality of machine-learned processing paths have a common encoding branch and separate decoding branches.
Assignees
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Classifications
Cell structures in vitro; Tissue sections in vitro · CPC title
from scanning electron microscope · CPC title
Training; Learning · CPC title
Image quality inspection · CPC title
Artificial neural networks [ANN] · CPC title
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Frequently asked questions
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- What does patent US12437396B2 cover?
- Various examples of the disclosure relate to techniques to count cells in a microscopy image and/or to determine a degree of confluence of the cells in the microscopy image. To that end, machine-learned algorithms are used.
- Who is the assignee on this patent?
- Zeiss Carl Microscopy Gmbh
- What technology area does this patent fall under?
- Primary CPC classification G06T7/0012. Mapped technology areas include Physics.
- When was this patent published?
- Publication date Tue Oct 07 2025 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
- What related patents are in patentsdb?
- We list 1 related publication on this page (citations in our corpus or others sharing the same primary CPC).