MILK10k Benchmark

MILK10k Benchmark consists of paired clinical close-up and dermatoscopic image for a set of lesions. The dataset’s metadata include age (in 5-year intervals), sex, anatomic site, and skin tone. Skin tone is categorized into six levels, ranging from very dark (0) to very light (5), intentionally distinct from the Fitzpatrick skin types to avoid confusion. Most patients had skin tones in the middle ranges. Diagnoses were mapped to a simplified classification based on the ISIC2018/2019 challenge and HAM10000 diagnostic categories. The dataset includes 11 broad diagnostic categories:

  1. Basal cell carcinoma (bcc)
  2. Melanocytic nevus (nv)
  3. Benign keratinocytic lesion (bkl)
  4. Squamous cell carcinoma/keratoacanthoma (sccka)
  5. Melanoma (mel)
  6. Actinic keratosis/intraepidermal carcinoma (akiec)
  7. Dermatofibroma (df)
  8. Inflammatory and infectious conditions (inf)
  9. Vascular lesions and hemorrhage (vasc)
  10. Other benign proliferations including collision tumors (ben_oth)
  11. Other malignant proliferations including collision tumors (mal_oth)

Although these broad diagnostic categories align with those in MILK10k, there can be different underlying granular diagnoses, primarily in the broad categories “other benign” and “other malignant proliferations”.

Furthermore, all images have been annotated using the MONET framework, with probabilities for the following concept term groups included in the metadata:

  1. Ulceration, crust
  2. Hair
  3. Vasculature, vessels
  4. Erythema
  5. Pigmentation
  6. Gel, water drop, fluid, dermoscopy liquid
  7. Skin markings, pen ink, purple pen

MILK10k Benchmark is the accompanying test set to the MILK10k dataset and covers the same diagnostic categories. MILK10k is available on the ISIC Archive.

Images were provided by the following institutions:

  • Department of Dermatology, Medical University of Vienna, Vienna, Austria
  • Medicine Faculty Department of Dermatology, Ankara University, Ankara, Turkey
  • Mayne Academy of General Practice, Medical School, The University of Queensland, Australia
  • Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, USA
  • Independent Researcher, 1000 Skopje, North Macedonia

Files

Description Size Type Action
The complete bundle of all images, metadata, and supplemental files related to this dataset. 31.6 MB ZIP
The metadata for this dataset. 94.9 KB CSV
Model input metadata containing non-diagnostic image-level attributes 231.8 KB CSV

Dataset Details

Published
DOI
10.34970/262082
Images
958
Attributions
  • MILK study team

Licenses

CC-BY-NC
CC-BY-NC

This content is free to use, modify, and share for non-commercial purposes, as long as you provide credit to the original creator.

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