Original text by the authors. Images and external links are unavailable on the intranet.

Provenance: official = uploaded by the dataset authors/institution; mirror = unmodified third-party copy; processed = third-party subset, slices or format conversion (may differ from the original). Licenses are as declared by the repository; staff check the original license of third-party copies before download.

BUSI — Breast Ultrasound Images Dataset

Re-hosted mirror of the Breast Ultrasound Images Dataset (Al-Dhabyani et al., 2020), collected at Baheya Hospital, Cairo, Egypt and originally distributed via the Cairo University Scholar page of co-author Aly Fahmy.

This mirror is intended for use with EasyMedSeg and provides:

A single canonical source (the original Cairo Univ. URL has unstable TLS).
Parquet schema with one row per image and a single binary mask.
For images with multifocal lesions, the multiple _mask_N.png files in the original release are merged into one binary mask via per-pixel logical OR (the convention adopted by the paper and by BUS-Set / Thomas et al. 2023).

Composition

Class	Images	Multifocal cases
benign	437	16
malignant	210	1
normal	133	0
Total	780	17

Image dimensions are variable (~190–719 px, average ~500×500 px). Source release is from 2018; 600 female patients, ages 25–75; GE LOGIQ E9 / E9 Agile B-mode.

Splits

BUSI has no official train/val/test split. This release ships a single train split. Downstream code is expected to define its own splits (BUS-Set provides reproducible ones).

Schema

Column	Type	Description
`image`	`Image`	Source PNG (RGB)
`mask`	`Image`	Binary mask (`L` mode, 0/255) — OR-merged across all mask files
`class_label`	`string`	`"benign"` / `"malignant"` / `"normal"`
`image_id`	`string`	e.g., `"benign (100)"`
`has_multifocal_lesion`	`bool`	`True` if the source had >1 mask file

Known data-quality caveats

Per Pawłowska et al. (2023, Data in Brief, PMC10293973): - ~235 duplicated images (~19%); 8 lesions appear in both benign and malignant folders (label leakage). - ~70 axilla (non-breast) images mis-categorized as breast. - 295 images with overlaid annotations (calipers, doppler markers, text) intersecting the lesion ROI. - ≥7 images contain a visible biopsy needle.

This mirror does not modify the source files (other than mask merging) — the above issues are inherited as-is. Cite Pawłowska et al. when reporting cleanups.

Citation

@article{Aldhabyani2020BUSI,
  title   = {Dataset of breast ultrasound images},
  author  = {Al-Dhabyani, Walid and Gomaa, Mohammed and Khaled, Hussein and Fahmy, Aly},
  journal = {Data in Brief},
  volume  = {28},
  pages   = {104863},
  year    = {2020},
  doi     = {10.1016/j.dib.2019.104863}
}

License

CC BY 4.0

Redistribution and commercial use are permitted under the terms below.

Source of the terms: https://pmc.ncbi.nlm.nih.gov/articles/PMC6906728/

Audit note (verbatim from the MedOtter dataset card):

Primary source (Data in Brief 2020, Al-Dhabyani et al.) states "open access article under the CC BY license (creativecommons.org/licenses/by/4.0/)". CC BY permits free redistribution + commercial use with attribution. HF tag "other" should be cc-by-4.0; only gap is the tag/attribution notice.

Please cite:

Al-Dhabyani W, Gomaa M, Khaled H, Fahmy A. Dataset of breast ultrasound images. *Data in Brief*. 2019;28:104863. doi:10.1016/j.dib.2019.104863

🗂️ MedOtter/BUSI