Dermatology Lesion Images
Buy and sell dermatology lesion images data. Moles, rashes, psoriasis, eczema — skin AI needs labeled images across every skin tone and condition.
No listings currently in the marketplace for Dermatology Lesion Images.
Find Me This Data →Overview
What Is Dermatology Lesion Images?
Dermatology lesion images are labeled photographs of skin conditions—moles, rashes, psoriasis, eczema, and skin cancers—captured via dermatoscopes, DSLR cameras, or mobile devices. These datasets are critical for training artificial intelligence models that detect and classify skin diseases. High-quality datasets include detailed metadata (diagnosis type, malignancy status, skin tone representation) and undergo rigorous expert review to ensure diagnostic accuracy and clinical utility. The market is driven by rising skin cancer incidence, growing prevalence of skin disorders, and widespread adoption of AI-integrated diagnostic tools in hospitals and clinics. Regulatory pathways like CE marking in Europe and CPT codes in the U.S. are expanding reimbursement for AI-assisted skin lesion evaluation, strengthening the financial case for data acquisition and model development.
Market Data
$815.5 million
U.S. Dermatology Imaging Market Size (2023)
Source: Grand View Research
13.50%
Projected Market CAGR (2024–2030)
Source: Grand View Research
~9,500 individuals
Daily Skin Cancer Incidence in U.S.
Source: Grand View Research (citing American Academy of Dermatology)
12,345 high-resolution dermatoscopic images from 1,627 patients
DERM12345 Dataset Size
Source: Nature
Who Uses This Data
What AI models do with it.do with it.
AI Model Development
Dermatology AI vendors and research institutes train machine learning models for automated skin cancer detection, classification, and risk stratification using labeled lesion images.
Clinical Decision Support
Hospitals and dermatology clinics deploy AI-assisted diagnostic tools to enhance accuracy and efficiency of skin lesion evaluation, supported by CPT codes for remote assessment.
Chronic Condition Management
Healthcare providers use image datasets to improve diagnosis and monitoring of inflammatory conditions such as psoriasis and eczema across diverse patient populations.
Pricing depends on the proposed terms
We do not have a verified, comparable price for your dataset. Consider the permitted uses, license term, exclusivity, provenance, coverage and quality. A seller asking price is a proposal, not an appraisal or guaranteed sale. Compare prices only when the source, date, currency, unit and license scope are known.
What Buyers Expect
What makes it valuable.valuable.
Image Quality & Resolution
Images must be clear, in-focus, and capture diagnostic features understandably. High-resolution dermatoscopic or DSLR images preferred; standardized lighting and framing conditions required.
Expert Annotation
Lesions require consensus clinical diagnosis by two expert dermatologists, histopathological confirmation, or documented follow-up. Malignant lesions must be biopsy-proven.
Metadata Completeness
Images must include classification hierarchy (super class, main class, sub-class, specific label), malignancy status, skin tone diversity, and copyright/licensing information for each record.
Ethical & Regulatory Compliance
Images must have proper patient consent, ethics review board approval, and exclude identifiable information. Unsuitable lesions (nails, mucosal, artifacts) must be removed.
Potential applications and organizations
Who's buying.buying.
Digital dermatoscopy devices and AI-assisted skin lesion evaluation; CE-marked under EU MDR.
Dermatology AI platform with regulatory approval (CE marking) for remote skin lesion assessment.
Dermatology imaging devices and broader healthcare diagnostic solutions.
Hand-held dermatoscope devices for clinical and research skin lesion imaging.
FAQ
Common questions.questions.
What drives demand for dermatology lesion images?
High daily incidence of skin cancer (approximately 9,500 individuals daily in the U.S.), growing prevalence of inflammatory skin disorders, and accelerating adoption of AI-integrated diagnostic tools in clinical settings. Regulatory approvals (CPT codes, CE marking) and expanding reimbursement are strengthening the financial case for data-driven dermatology solutions.
Why is skin tone diversity critical in these datasets?
AI models trained on homogeneous datasets perform poorly on underrepresented skin types, leading to diagnostic errors and health inequities. Buyers explicitly require datasets spanning multiple skin tones and ethnic backgrounds to ensure model fairness and clinical utility across all patient populations.
What makes a lesion dataset valuable for commercial buyers?
Scale (thousands of images from diverse patients), expert annotation (consensus diagnosis + histopathology confirmation), complete metadata (classification hierarchy, malignancy status), high image quality, and regulatory compliance (ethics approval, proper consent). Datasets meeting these standards support regulatory submissions and clinical deployment.
How do I ensure my images meet clinical standards?
Follow standardized acquisition protocols (consistent lighting, centered framing, dermatoscope or DSLR capture). Have two expert dermatologists review each image and confirm diagnosis. Document malignancy via biopsy, follow-up, or clinical consensus. Remove blurred, unsuitable, or ethically non-compliant images. Include complete metadata and obtain explicit patient consent.
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Describe your dermatology lesion images and the uses you are authorized to offer. Price, legal suitability, and buyer interest require separate evaluation. No match or sale is guaranteed.
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