Spatial Transcriptomics Imaging Patents: Leaders & White Space 2026
A data-backed look at spatial transcriptomics imaging patents: who leads filings, how the technology composition breaks down across IPC classes, and where claim space remains open.
Filing growth = 2021 (14 records) → 2024 (13); 2024 is the last year we treat as complete. Top-5 share = the 5 largest assignees ÷ all 82 records in scope (CR5), not the ranked leaders only.
What the spatial transcriptomics imaging patent record shows
Spatial transcriptomics imaging sits at the intersection of tissue-based molecular assays and computer vision: it captures gene or protein expression while preserving where in a tissue section that signal occurred. The 82 records in scope span filings from 2015 through the partial 2026 year, and cover both the imaging hardware and instrumentation side and the machine-learning pipelines used to reconstruct, label and interpret the resulting spatial data. Patent families, rather than raw publication counts, are the fairer unit here because they filter out repeat continuations and multi-jurisdiction refiling of the same underlying invention — the ranking used on this page counts by family.
Filing activity is not evenly split between assay chemistry and image analysis. A large share of records fall under image and video recognition and image-data-processing classes, alongside a smaller but still substantial cluster in bioinformatics and material analysis. That split matters for anyone scoping freedom-to-operate: the crowded ground is now as much about how spatial data is processed and labelled as about how it is generated in the first place.
Let an AI agent run this analysis on your own technology
Pick a task. Every answer cites the patents behind it.
Filing trends and technology composition
Two views of the same 82 records: how filing volume has moved year over year, and how those records distribute across IPC subclasses. Because a single record can carry several classes, the class shares below sum to more than 100% of the record total.
Filing trend: rise, 2023 peak, then plateau
Filings climbed from zero in 2017 to a peak of 23 records in 2023. Between 2021 (14 records) and 2024 (13 records) — the last year that can be treated as complete once publication lag is accounted for — volume moved -7%, consistent with a field that has built up a base of activity rather than one still accelerating.
Publication lags filing by roughly 18 months, so 2025 onwards are still filling in. Growth rates on this page therefore end at 2024; running them to the last bar would understate the field.
Technology composition: imaging and computation lead
G06V (image/video recognition) appears in 45.1% of the 82 records and G06T (image data processing & generation) in 37.8%, ahead of G16B bioinformatics at 26.8% and G01N material analysis at 22.0%. C12Q and C12N, the classes closest to wet-lab nucleic acid and genetic-engineering methods, sit lower at 15.9% and 9.8% respectively — evidence that claim density has migrated toward the computational layer of the pipeline.
Shares are the percentage of the 82 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Spatial Omics: Spatial Transcriptomics Imaging Patent Landscape with Eureka
This page is one run against one query. Ask Eureka your own question about spatial omics: spatial transcriptomics imaging patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaThe most-cited records in the field
Machine-learning-enabled imputation of spatial omics data based on histopathology image data
The disclosure describes machine learning techniques for generating synthetic spatial omics data from histopathology images: a system that takes a histopathology image of a diseased tissue region and generates a synthetic spatial omics image depicting stained structures, effectively imputing spatial omics readouts where direct measurement was not performed.Filed by Insitro, Inc., published 2025-05-01 — illustrative of a shift toward inferring spatial omics signal computationally rather than only measuring it directly.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US11713480B2 | Materials and methods for localized detection of nucleic acids in a tissue sample | 37 |
| 2 | US20230306761A1 | Methods for identifying cross-modal features from spatially resolved data sets | 32 |
| 3 | WO2021127019A1 | System and method for acquisition and processing of multiplexed fluorescence in-SITU hybridization images | 21 |
| 4 | WO2022051546A1 | Methods for identifying cross-modal features from spatially resolved data sets | 16 |
| 5 | WO2022272014A1 | Computational techniques for three-dimensional reconstruction and multi-labeling of serially sectioned tissue | 10 |
| 6 | CA3190344A1 | Methods for identifying cross-modal features from spatially resolved data sets | 8 |
| 7 | US20250139765A1 | Computational techniques for three-dimensional reconstruction and multi-labeling of serially sectioned tissue | 6 |
| 8 | US20220044397A1 | Systems and methods to process electronic images to provide image-based cell group targeting | 6 |
| 9 | US20210199584A1 | System and method for acquisition and processing of multiplexed fluorescence in-situ hybridization images | 5 |
| 10 | US20210182531A1 | Registration techniques for multiplexed fluorescence in-situ hybridization images | 5 |
Ranked by citation count within the searched corpus. Citation counts favour older filings that have had more time to accumulate references, so read this as a signal of influence rather than of current commercial relevance.
Each row carries its publication number; clicking a row searches Eureka by that number.
Put your own technology through the same analysis
Eureka on the web
When you want the answer in the next five minutes.
The agent works the prompt against patents and technical literature, citing every source.
Run your analysis now →MCP server & REST API
When it has to run inside your own pipeline.
Patent search, landscape analysis and assignee resolution as MCP tools. Drop them into any agent framework, or call REST directly.
Browse MCP servers →What the concentration and composition figures mean for strategy
The ranking and the class breakdown point to a field where a handful of institutions built an early lead in imaging and computational claims, while wet-lab assay chemistry classes remain comparatively less contested.
A top-heavy but not closed field
The top 5 assignees combine for 52.4% of all 82 records in scope, and the top 10 extend that to 76.8%. That leaves roughly a quarter of filings spread across a long tail of single- or few-filing entrants — room to move exists, but new filers are working around claim positions already staked out by the leaders.
Computation, not just chemistry, is the crowded ground
G06V and G06T together touch a large share of records, ahead of bioinformatics (G16B, 26.8%) and the wet-lab-adjacent C12Q and C12N classes (15.9% and 9.8%). Anyone assuming the open ground is in image processing should check the assignee overlap in those classes before filing there.
Growth has levelled, not collapsed
Filings rose to a peak of 23 in 2023, then eased slightly, with 2021's 14 records compared to 2024's 13 marking a -7% change over that span. Because publication lags filing by around 18 months, years after 2024 are still filling in and should not be read as a decline.
Co-filing is rare so far
Only two co-assignee pairs appear in the dataset, the strongest linking a university and a regional health authority across three shared records. Most activity in this field is filed by a single assignee rather than through joint ventures or cross-institution agreements.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to spatial omics: spatial transcriptomics imaging patent landscape, with the prior art for and against each one.
| Assignee | Co-assignee | Shared families |
|---|---|---|
| Aarhus University | REGION MIDTJYLLAND | 3 |
| The General Hospital Corporation | Massachusetts Institute of Technology (MIT) | 1 |
The strongest co-assignee link in the dataset pairs a university with a regional health authority across three shared records — a research-hospital pattern rather than a corporate joint venture.
Where to take this analysis
The figures above describe the shape of the field. Turning that into a filing or licensing decision means drilling into specific claim sets and the assignees behind them.
Map claim boundaries before drafting
Use the most-cited records as a starting point to understand what the leading assignees have already claimed in image reconstruction, multiplexed detection and cross-modal feature extraction before scoping new claims.
Explore claims in EurekaTrack the under-claimed branches
Bioinformatics and wet-lab classes carry a smaller share of records than the imaging classes — worth checking whether that reflects genuine white space or simply less mature filing activity.
Run a white space search in EurekaWatch the long tail
With roughly a quarter of records held outside the top 10 assignees, new entrants are still finding room to file. Monitoring newly published applications from smaller filers can surface emerging approaches early.
Set up monitoring in EurekaFrequently asked questions
It refers to inventions that capture gene or protein expression data while preserving its physical location within a tissue sample, and then process that data as an image. In patent terms this spans two areas: the instrumentation and assay chemistry used to generate spatially resolved molecular signal, and the computational methods — image recognition, reconstruction, cross-modal feature extraction — used to interpret it. The dataset behind this page (82 records) captures both, which is why classes like G06V and G06T show up alongside bioinformatics and material-analysis classes.
The ranking returned for this dataset covers 26 companies and institutions, counted by patent family. The leader holds 14 records, and filing is fairly concentrated: the top 5 assignees together account for 52.4% of all 82 records in scope, and the top 10 account for 76.8%. That still leaves close to a quarter of filings spread across a long tail of smaller filers, so the field is concentrated but not closed to new entrants.
Filing activity rose from zero in 2017 to a peak of 23 records in 2023, then eased. Comparing 2021 (14 records) to 2024 (13 records) — the most recent year that can be treated as complete — shows a -7% change, suggesting the pace has levelled off rather than continuing to accelerate. Note that publication typically lags filing by around 18 months, so figures for 2025 and 2026 will rise as more applications publish and should not yet be read as a slowdown.
Image and video recognition (G06V) appears in 45.1% of the 82 records and image data processing (G06T) in 37.8%, making computational claims the densest part of the landscape. Bioinformatics (G16B) follows at 26.8% and material analysis and testing (G01N) at 22.0%, with nucleic-acid and enzyme-related classes (C12Q, C12N) further behind at 15.9% and 9.8%. Because a single record can carry multiple classes, these figures overlap and should be read against the 82-record total, not against each other.
The class distribution suggests the wet-lab and bioinformatics side of the pipeline — C12Q, C12N and, to a lesser extent, G16B — carries a smaller share of the 82 records than the imaging and computation classes. That does not guarantee open claim space, but it does mean fewer filings have staked out ground there relative to G06V and G06T. Co-filing is also rare across the dataset, with only two identified co-assignee pairs, hinting that cross-institution collaboration claims are underused generally.
Research Spatial Omics: Spatial Transcriptomics Imaging Patent Landscape in depth with Eureka
Go past this page: query the whole spatial omics: spatial transcriptomics imaging patent landscape corpus yourself, in your own scope.
Every answer comes back with patent numbers you can open.
Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.