Dataset Overview
Definition:Dermoscopy Images and Pathology Diagnostic Reports Datasetis provided byChangsha Langhui Information Technology Co., Ltd.Integrated high quality skin data. Covers skin lens images, skin-dermal clinical photographs and standard pathological gold diagnostic reports, creating image-clinical-pathological data links at three levels, and providing core training language for skin-disease AI screening and diagnosis.
| Dataset Name | Dermoscopy Images and Pathology Diagnostic Reports Dataset |
| Total Data Volume | A lot of high-quality skin mirror images |
| Data Type | Image (skin mirrors + clinical photos) + pathological report |
| Data Source | Resale |
| License Type | Sublicensing Complete authorization documents are attached |
| Core Features | Standard medical examination, age, skin damage, preliminary clinical diagnosis |
| Covered Disease Categories | Melanoma, base cell cancer, scab cell cancer, lipid perfluent agularization, moles, etc. |
Core Data Fields
Each piece of data contains complete structured fields that cover everything from raw data to specialized diagnostics.
| Field Category | Field Count | Typical Fields |
|---|---|---|
| Skin mirror image | 6 | Skin mirror image, magnification multiple, image resolution, collecting device model |
| Clinical photos | 4 | Macro photographs of skin lesions, lesion site annotation, shooting distance and lighting conditions |
| Pathology Report | 10 | Full pathology diagnosis (King standard), tissue type, celerity, leaching depth (Breslow), silk division rate |
| Patient Information | 5 | Age, gender, lesion site, disease duration, preliminary clinical diagnosis (all de-identified) |
| Tab label | 3 | Benign-Malignant Classification, ABCDE Feature Scoring, 7-Point Checklist Scoring |
Data Sample Showcase
The following is a de-identified structured JSON sample illustrating the typical data format.
{
"case_id": "DERM-2023-0004521",
"meta": {"age": 58,"gender": "male","lesion_site": "sample value","duration": "6sample"},
"dermoscopy": {"type": "sample value","features": ["sample","sample","sample"]},
"pathology": {"diagnosis": "Unstable angina","breslow_depth": "2.4mm","ulceration": true,"mitotic_rate": "4/mm²","tnm_stage": "T3aN0M0"},
"clinical_dx": "sample value","final_label": "sample value"
}AI Application Scenarios
Skin screening AI
Train CNN/Transformer models based on skin mirror images to achieve automatic classification and benign identification of common skin diseases, applicable to large-scale skin cancer screening.
Early Detection of Malignant Melanoma
The gold standard pathology control data are used to train early detection models for melanoma, combining ABCCE features with a seven-point checklist to improve the accuracy of early diagnosis.
Assessment of skin mirror image quality
The multi-light, multi-equipment-type skin lens images are used to train the image quality automatic assessment model to assist remote dermal consultations.
Remote dermatology AI
The rich skin mirror images and clinical data are used to train remote skin systems in AI to address the shortage of dermal doctors at the grass-roots level.
Pathology-Image Correlation Analysis
The pathogen standard and skin lens image correlation data are used to train pathological prediction models, providing pre-invasive pathological type prognosis prior to the operation.
Escular AI teaching
A wealth of cases and data is used in the AIS teaching system of dermatology, which assists inpatients and medical students in identifying typical and unusual skin disorders.
Frequently asked questions
Need for customised medical data programs?
Changsha Langhui Information Technology Co., Ltd. The DataAssetsAPI platform is dedicated to providing high-quality, compliant medical data assets for AI companies and scientific research institutions. Cooperate with 50 + hospitals, including Fudan 100 type hospitals.
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