Reliable AI-Assisted OCT Interpretation
Expert Analysis: Managed by certified, rigorously trained image graders.
Secure Infrastructure: Supported by a seamless, fully encrypted database link.
Client-Centric Process: Focused on transparent communication and flexible study workflow.
Secure sharing De-identified data only
FOR RESEARCH & INVESTIGATIONAL USE ONLY
FREE, NO COMMITMENT
See it on your own data — free
Send one de-identified volume. We run it and send your sample report, so you know exactly what you'd be licensing.
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Upload via a secure link
Send a link to one de-identified OCT volume via the form below.
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We run the segmentation
Our team runs your scan through JDAe, our automated segmentation engine.
Get your report next day
Receive a sample report - thickness maps, ETDRS-grid values, and full macula data.
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Book a call if you're ready to license for in-house use
Like what you see? License the tools and run them yourself, unlimited, in-house.
THE SOFTWARE
Two tools, one workflow
JDAe - Data analysis with AI-based segmentation
Get structured, trial-ready output in one pass
Read Cirrus, Spectralis, and Neuro-i OCT data
Segment 8+ retinal layers automatically
Measure average thickness for 9 standard ETDRS subfields and thickness map
Export deterministic results in PDF report
JAM - Manual Correction
Precise by Hand, Simple by Design
Correct an existing layer boundary
Annotate pathological regions
Export the corrected data in JSON file
"Streamline clinical analysis with automated processing of artifact-free retinas, targeted human adjudication for pathological scans, and a 21 CFR Part 11 compliant end-to-end audit trail."
INCLUDED WITH A LICENSE
See it on your own data - free
What you get
Send one de-identified volume. We run it and send your sample report, so you know exactly what you'd be licensing.
Cross-vendor analysis
One engine across Cirrus and Spectralis, so multi-site data is comparable.
Structured outputs
Per-layer thickness, ETDRS sectorization, PDF report + CSV
Human-in-the-loop
QC
Correct the algorithm's blind spots on retinas with significant pathology.
Audit trail
Grader identity, timestamps, and edit history on every corrected dataset.
Clinically Validated
Built on peer-reviewed research
JuneBrain's automated segmentation is built on a deep-learning method published in Medical Image Analysis (2021). It produces smooth, anatomically ordered retinal layer surfaces with sub-pixel accuracy, and was validated against expert manual delineation on healthy, multiple sclerosis, and diabetic macular edema OCT data - meeting or exceeding established methods.
He Y, Carass A, Liu Y, et al. Structured layer surface segmentation for retina OCT using fully convolutional regression networks. Med Image Anal. 2021;68:101856.
PRICING
Simple, transparent pricing
One plan for research and investigational use. Annual license, billed yearly.
FOR RESEARCH & INVESTIGATIONAL USE ONLY