Datasets:
File size: 3,970 Bytes
ceb2a2b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 | ---
license: cc-by-4.0
task_categories:
- image-segmentation
tags:
- medical
- ultrasound
- breast
- segmentation
- busi
size_categories:
- n<1K
---
# 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](https://github.com/) 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](https://pmc.ncbi.nlm.nih.gov/articles/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
```bibtex
@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}
}
```
<!-- licence section rendered from the MedOtter card, 2026-09-06 -->
## 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
```
|