Case
Measuring skull deformation
Skully Care measures skull deformation in babies from a single photo. Twentynext developed the algorithm that automates that measurement; their app is used by more than 900 therapists in 30 countries.
Sector
From image analysis in the hospital to monitoring in research barns. Eight of our eighteen cases sit in this domain, alongside academic hospitals, healthcare companies and Wageningen University.
The situation
In this domain the data rarely arrives in tidy rows and columns. It is an IHC image, a retinal photograph, a picture of an infant skull, or a series of measurements from a barn. Two recordings of the same phenomenon also look different: staining varies, lighting varies, and image size varies with it.
That variation is the actual work. In the tumour cell detection for the Antoni van Leeuwenhoek, adaptive colour analysis sits in the system precisely because IHC staining differs per specimen, and image filtering runs first to reduce the chance of errors. A model that works on laboratory images and stumbles in practice is not a rarity here but the normal starting point.
What a model delivers here is a preliminary assessment, not a verdict. In the tumour cell detection the judgement stays with the pathologist; what the system provides is a consistent assessment of images that would otherwise be reviewed one by one. Reproducibility therefore matters more than the last few percent of accuracy.
We believe technology should be reliable, transparent and explainable, particularly where decisions affect people. In healthcare that is not a principle we add; it is a requirement the sector already sets.
Roles
Twentynext works in four ways: advice, people, projects and maintaining what runs. In this domain these three occur most often. What advice means here, you will find under data consultancy in healthcare.
Turning image and signal into a repeatable assessment
Models that assess images or measurement series in a way that is repeatable and stays traceable: which processing was applied, and on what the decision was based.
Research with clinical and academic partners
Part of this work is research, with hospitals, healthcare companies and universities. Part of our R&D is exactly that: not finished yet. That is a status, not an interim phase that resolves itself.
An algorithm that runs inside someone else’s product
Sometimes the result is not a system of our own but a component: the algorithm Twentynext developed for Skully Care runs inside their app.
Evidence
Case
Skully Care measures skull deformation in babies from a single photo. Twentynext developed the algorithm that automates that measurement; their app is used by more than 900 therapists in 30 countries.
Case
Research with the Antoni van Leeuwenhoek: analysing IHC images automatically and assessing clusters for severity and aggressiveness. The judgement stays with the pathologist.
Solution
Assessing images with AI: where this helps and where it does not, and what is needed before a model becomes usable in practice.
Scope
We build algorithms and systems. The clinical judgement stays with the healthcare professional, and that is not a formality: our systems deliver a preliminary assessment that a doctor or researcher then weighs.
We are not a manufacturer of medical devices and do not present ourselves as one. Certification, clinical validation and market approval sit with the party bringing the product to market; we deliver the data and AI work underneath.
Part of what is described here is research rather than a delivered product. We prefer to say that beforehand rather than afterwards. If you are working on a question in this domain and the data or AI side is missing, that is the conversation we are glad to have.
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Work with us
The people who build it also run it afterwards. Eindhoven, since 2014.
Martijn van Grieken
Director Data & AI
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