ENGINEERING · IMAGING · ARTIFICIAL INTELLIGENCE
From automated microscopy to retinal imaging, microscopIA brings engineering and clinical expertise together to study tools that could expand access to specialist capacity.
WORK WITH MICROSCOPIA
For teams with clinical images, data or an engineering need.
Proposed scope: data preparation, model development, prototype requirements and testing.
A description of the data, available permissions and intended use.
Discuss this project →For investigators and developers studying technology performance.
Proposed scope: study design, evaluation plan, performance analysis and limitations.
System version, target population, metrics and available evaluation data.
Discuss this project →For institutions considering adoption of a healthcare technology.
Proposed scope: economic evaluation, implementation analysis and decision evidence.
Care setting, comparator, costs and the decision to be informed.
Discuss this project →Research collaboration requires agreed scientific contributions and responsibilities. Paid scientific services are quoted by scope and deliverables. Technology development and validation require specific plans, permissions and evaluation criteria; neither implies regulatory authorization.
Send a nonconfidential brief. We review feasibility, disciplines, timing and budget before agreeing the project.
Two programs. A shared purpose.
01 / ROPA device-and-AI research program to study image acquisition and identification of findings that need review by a ROP-trained ophthalmologist.
Research and development ↓02 / MICROSCOPYAn engineering prototype exploring image acquisition and software-assisted review for malaria research.
Research and development ↓PROPOSED DEVELOPMENT PATHWAY
Technology evidence · human-led by design
This evidence family documents concepts, physical prototypes, task-specific development benchmarks, validation gaps and human decision boundaries. microscopIA develops technology for settings where specialist capacity is limited without presenting investigational systems as clinical products.
microscopIA is developing an integrated research system for retinal imaging in preterm infants. The device is intended to support a high-resolution camera, primarily a compatible smartphone, to improve inspection and capture of infant retinal images.
Research models analyze de-identified retinal images to study image quality and features of retinopathy of prematurity (ROP). The intended goal is to help identify infants with concerning findings or higher risk for referral to a ROP-trained ophthalmologist, who retains diagnosis and treatment decisions. Future use is being evaluated for appropriately trained neonatologists, neonatal nurses and physicians, including general practitioners where permitted, working under approved institutional protocols and local scope-of-practice rules.
Ungradable image or failed acquisition → repeat or escalate under the approved protocol. There is no AI-created ‘no referral’ pathway.
Latest supplied AI development record
Source last modified 19 November 2025. Values are shown by model task because the supplied record does not establish performance of an integrated device–AI system.
Stage-related image classification
92.03%Accuracy · reported scoreGCViT · 1,099 public-dataset imagesPlus-disease classification
93.10%Accuracy · reported scoreResNet50 · public development datasetVessel segmentation
76.81%Intersection over UnionU-Net · HVDROPDBThese are early model-development measures, not a grade for the complete device or a prediction for an individual infant.
The source reports the stage and plus accuracy values without a percent sign. This page displays them using the conventional 0–100 percentage scale for readability; confirm the original analysis record before reusing the figures. These are separate public-dataset development tasks with incomplete evaluation details. They are not directly comparable, externally or clinically validated, or evidence of device-level performance. No specificity, AUROC or confidence intervals are claimed.
A physical microscopIA prototype connecting automation, imaging and review by laboratory professionals. Explore the demonstration, the research objective and the validation still needed.
The public video documents a physical microscopy prototype. The program investigates automated image acquisition and software-assisted flagging of candidate fields, quality issues or samples for review by trained laboratory professionals. It does not confirm or exclude malaria, establish species or parasite density, choose treatment, or replace laboratory quality assurance and clinical judgement.
Any future application to another microscopy-based tropical disease requires its own intended use, dataset, validation plan and regulatory assessment.
A physical prototype and its public video demonstration. The video documents engineering development; it is not a diagnostic evaluation.
Automated image acquisition and software-assisted flagging of candidate fields or quality issues for review by trained laboratory professionals.
Intended-use performance, reproducibility, safety, usability and independent validation with appropriate samples and professionals. These stages are not presented as completed.
Laboratories, malaria experts, engineers and institutions can propose a research scope: reference methods, acquisition evaluation, authorized data, human factors or validation. Responsibilities, resources, ethics, data access and intellectual property are agreed first.
Research priorities start with settings where specialist people and infrastructure are scarce.
Technology may support acquisition and prioritization; qualified professionals remain responsible for decisions.
Safety engineering, usability, governance, training and independent validation precede clinical use.
Collaboration areas: ROP and pediatric ophthalmology, neonatology, optics and imaging, human factors, device engineering, clinical-AI validation, laboratory microscopy, quality systems and regulation.
Explore responsible fundingSCIENTIFIC AND TECHNOLOGY COLLABORATION
Bring a clinical need, technical capability or evaluation proposal. Feasibility, responsibilities and scope are agreed before work begins.
Define intended use, service needs and the evaluation setting.
Explore imaging, automation, data quality and model evaluation.
Propose resources, infrastructure or collaboration for a defined development phase.
RESEARCH · DEVELOPMENT STAGE
The work shown here is investigational. Qualified professionals retain clinical decisions. Each system needs evidence appropriate to its intended use, safety assessment and applicable regulatory review before clinical deployment.
