SITE 01PICO
Pico + CO2 multi-device stack
Cutera Enlighten 532
532 nm
Routes discrete epidermal pigment such as freckles and solar lentigines into a 532 nm picosecond pathway.
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Clinical validationPhysician AI · Laser protocol intelligence
DermatoScan AI
Structures pigmentation protocols by device, lesion, and skin type.
DermatoScan considers photographs, lesion context, Fitzpatrick skin type, and the clinic’s device inventory together. It then organizes differential considerations, risk flags, device-routing options, and reference parameter ranges for clinician review. The knowledge base is expanding from pigmentation into CO2- and picosecond-laser scar protocols.
Knowledge base status
Early validation cases50+
Pigmented-lesion knowledge base11
Laser / energy devices11
Clinic operating contexts reflected3
Demo
DermatoScan AI demo
See the actual product flow: lesion input, analysis screen, agent consultation, and protocol references inside one review workflow.
The core is the clinical knowledge base.
DermatoScan runs on a versioned clinical knowledge base, device-specific protocol library, and physician-review output structure. AI does not make diagnosis or treatment decisions; it organizes candidate diagnoses, risk flags, device routing, and parameter references for clinician review.
Problem
The more lasers a clinic owns, the more important the selection standard becomes.
The same lesion may require a different approach depending on pigment depth, skin type, stimulation risk, and available devices. Yet the criteria behind those choices often remain tacit knowledge.
01
Variation in lesion-device matching
Freckles, lentigines, melasma, PIH, ABNOM, and Hori-type lesions differ in depth and response to stimulation. Wavelength and pulse regime therefore change the clinical review path.
02
Opaque device selection
Clinics with multiple laser and energy devices need a standard that explains why a device is being considered. If the standard lives only in someone’s head, choices and explanations drift.
03
Unstandardized know-how
When expert experience is not captured as an institutional asset, new clinicians repeat the same trial and error. DermatoScan turns decision criteria into reusable protocol structures.
Clinical protocol engine
From image review to a protocol pathway
DermatoScan AI reads lesion context and device inventory together, then surfaces physician-reviewable device routing and protocol references.
STEP 01
11 lesions × 11 devices connected
The product connects the pigmented-lesion knowledge base and device library in one structure. After classifying lesion type, depth, and risk context, it narrows the clinically reviewable options inside the clinic’s available devices.
STEP 02
Reviewable output structure
Outputs are separated into candidate diagnosis, differential and risk flags, device-selection rationale, parameter reference ranges, and patient-explanation points. Clinicians review the context, then accept, modify, or reject.
Protocol routes
Routing that sees lesion, depth, and device together.
This is not a fixed four-device matrix. It is a routing structure that reads each clinic’s device inventory together with lesion characteristics and is adjusted during implementation.
| Routing axis | Review flow |
|---|---|
| Pigment depth | Distinguishes epidermal, dermal, and mixed pigment, sending stimulation-sensitive lesions such as melasma and PIH into more conservative paths. |
| Device inventory | Maps picosecond, Q-switched, long-pulsed, and CO2 devices according to each clinic’s actual equipment. |
| Safety gates | Surfaces malignancy concerns, keloid or PIH risk, Fitzpatrick type, pregnancy, medication, and other conditions before treatment planning. |
| Protocol reference | Organizes parameter ranges, pretreatment, aftercare, and explanation points as references for final physician judgment. |
Registered laser library
11 laser and energy devices, shown in real operating context.
DermatoScan’s device library is more than a list of equipment. It connects each clinic’s inventory, wavelengths, pulse regimes, and primary indications to the routing framework.
SITE 01PICO
Pico + CO2 multi-device stack
Cutera Enlighten 1064
1064 nm
Supports melasma toning, PIH, ABNOM, and Hori-type pathways where depth and stimulation risk both matter.
SITE 01PICO
Pico + CO2 multi-device stack
Cutera Enlighten 670
670 nm
Adds a selective-pigment route that complements the 532 and 1064 nm choices.
SITE 01LONG
Pico + CO2 multi-device stack
Lutronic Clarity Pro 755
755 nm
Covers hair-removal and selected vascular-support contexts around pigment treatment planning.
SITE 01LONG
Pico + CO2 multi-device stack
Lutronic Clarity Pro 1064
1064 nm
Organizes genesis, vascular pretreatment, and darker-skin hair-removal pathways.
SITE 01CO2
Pico + CO2 multi-device stack
SooDo CO2 Laser
10,600 nm
Covers thick seborrheic keratosis, skin tags, raised lesion removal, and the CO2-based scar expansion loop.
SITE 02PICO
Pigment + vascular + hair-removal stack
Cynosure PicoSure
755 nm
A picosecond Alexandrite route for pigment toning, tattoo, scar, and pore workflows.
SITE 02Q-SW
Pigment + vascular + hair-removal stack
Lutronic Hollywood Spectra
1064 / 532 nm
Handles Q-switched routes for melasma toning, PIH, pigment spots, and carbon peeling.
SITE 02LONG
Pigment + vascular + hair-removal stack
Cutera Excel V (original)
1064 / 532 nm
Adds vascular, rosacea, telangiectasia, and genesis support into the same review context.
SITE 02LONG
Pigment + vascular + hair-removal stack
Cynosure Apogee+
755 nm
A hair-removal-only route, explicitly separated from PicoSure despite sharing 755 nm wavelength.
SITE 03PICO
Multi-wavelength pico platform
Lutronic PicoPlus
1064 / 532 / 595 / 660 nm
A multi-wavelength platform covering pigment, tattoo, vascular, scar, and pore workflows.
Development loop
Expanding from pigmentation into CO2 and scar protocols
Pigmentation routing is the current focus, while the knowledge base is expanding into CO2 focal ablation, fractional CO2, acne scars, and pore, scar, and rejuvenation pathways. Clinician feedback and agent-assisted development continuously refine the system.
Current focus: pigmentation routing
The first productized layer covers pigmented-lesion assessment and device selection across pico, Q-switched, long-pulsed, vascular, and hair-removal contexts.
Expansion axis: CO2 and scars
Raised-lesion removal, CO2 focal ablation, fractional CO2, acne-scar care, and pore and scar workflows are next in the knowledge-base and validation roadmap.
Human-in-the-loop improvement
Clinician review, case logs, knowledge-base updates, and development agents feed one loop so the protocol tool can become more precise over time.
Validation
Protocol AI being validated in real clinical workflows
DermatoScan is not a lab-only demo. It is specialty AI undergoing validation in outpatient care.
50+
Early validation cases
11
Pigmented-lesion knowledge base
11
Laser / energy devices
3
Clinic operating contexts reflected
More than 50 early validation cases across freckles, lentigines, and melasma are used to observe how the selection standard behaves in actual outpatient care.
As of knowledge base v2.2.0, pigment, vascular, hair-removal, CO2, and partial scar/pore routes are managed through device documents and protocols.
Outputs are provided for clinician review. AI does not replace diagnosis or treatment decisions; it organizes the materials required for judgment.
The validated structure is intended to become the baseline for future vertical medical AI products joining the platform.
Platform
A specialty engine in the clinical-intelligence layer
DermatoScan AI sits in the clinical-intelligence layer and shares one patient state with the other engines. Interpretation and the final call stay with the physician.
Specialty-AI layer
It provides depth in skin-pigmentation and laser protocols. Together with WoundScan AI, it defines the validation pattern for vertical medical AI.
Built on horizontal infrastructure
Dockie-talkie reduces language barriers, while Clinical Copilot strengthens reasoning and documentation context. DermatoScan adds dermatology and laser expertise on top.
Standard for third-party AI onboarding
The data structure, physician-review model, and protocol management validated in practice become the baseline for third-party vertical medical AI joining AetherHeal.
Impact
What adoption can change
DermatoScan AI turns laser-treatment know-how from individual experience into a reviewable institutional asset.
Standardized device selection
Lesion-to-device routing becomes explicit, helping clinicians review the same lesion with a more consistent standard.
Shorter learning curve
New clinicians can start from a verified knowledge base instead of guessing senior clinicians’ tacit criteria.
Experience becomes an asset
Cases and feedback from the field accumulate inside the knowledge-base and protocol structure, becoming long-term institutional capability.
FAQ
Frequently asked questions
Common questions when evaluating DermatoScan AI.
No. DermatoScan AI does not decide diagnosis or treatment. It organizes lesion, device, skin type, and risk-signal information for clinician review. Final judgment always remains with clinicians.
It is built from 11 pigmented lesions, 11 laser and energy devices, early validation cases, device-specific protocol documents, and clinician feedback. Sensitive lesions such as melasma include pretreatment and stimulation-risk context.
Yes. DermatoScan is not a fixed four-device matrix. It is a routing structure that adapts to each clinic’s device inventory, procedure standards, and review scope.
Pigmentation AI is the current focus. CO2 focal ablation, fractional CO2, acne-scar care, and pore, scar, and rejuvenation pathways are being added to the development and validation loop. We do not claim guaranteed treatment outcomes.
DermatoScan AI sits in Layer 2, the specialty-AI layer of AetherHeal’s platform. It runs on Layer 1 infrastructure such as Dockie-talkie and Clinical Copilot, connecting interpretation, documentation, reasoning support, and specialty protocols.
DermatoScan runs on a versioned clinical knowledge base, device-specific protocol library, and physician-review output structure. It does not replace decisions; it organizes evidence and candidate flows for clinicians to review.
Considering DermatoScan AI for your clinic?
We can design the pilot scope around your device inventory and clinical workflow.
Contact us