---
license: cc0-1.0
task_categories:
- image-segmentation
tags:
- breast-cancer
- breast-ultrasound
- image-segmentation
- nnUNet
size_categories:
- n<1K
---
# 🎗️ Breast Ultrasound Dataset for nnU-Net v2

This repository contains the **formatted dataset** for **breast ultrasound segmentation**, prepared for use with **nnU-Net v2**. The dataset has been preprocessed and structured according to the **nnUNet v2 dataset format** for easy training and inference.  

## 📌 Dataset Overview  

- **Original Dataset**: [Breast Ultrasound Images Dataset](https://www.kaggle.com/datasets/aryashah2k/breast-ultrasound-images-dataset)
- **Task**: Breast Ultrasound Segmentation
- **Input Data**: 2D ultrasound images of the breast
- **Target Labels**: Segmentation masks for lesion regions
- **Dataset ID for nnU-Net**: 101
- **Dataset Name for nnU-Net**: Breast

---

## 📁 Folder Overview

### Original Dataset (combined multi-masked images)

#### ℹ️ About

The dataset comprises breast ultrasound images obtained from women aged 25 to 75 years. The data collection took place in 2018 and includes records from 600 female patients. It contains a total of 780 images, with an average resolution of 500×500 pixels, all stored in PNG format. Each ultrasound image is accompanied by its corresponding ground truth segmentation. The images are classified into three categories: normal, benign, and malignant.

#### 📊 Statistics
- 📸 Total Images: 780
- ✅ Normal: 133
- 🌿 Benign: 437
- ⚠️ Malignant: 210

```bash
Breast_Ultrasound_Images/
├── benign/
│   ├── breast_001_0000.png
│   ├── breast_002_0000.png
│   ├── ...
│   └── breast_437_0000.png
├── benign_masks/
│   ├── breast_001.png
│   ├── breast_002.png
│   ├── ...
│   └── breast_437.png
├── malignant/
│   ├── breast_438_0000.png
│   ├── breast_439_0000.png
│   ├── ...
│   └── breast_647_0000.png
├── malignant_masks/
│   ├── breast_438.png
│   ├── breast_439.png
│   ├── ...
│   └── breast_647.png
├── normal/
│   ├── breast_648_0000.png
│   ├── breast_649_0000.png
│   ├── ...
│   └── breast_780_0000.png
└── normal_masks/
    ├── breast_648.png
    ├── breast_649.png
    ├── ...
    └── breast_780.png
```

### Formatted Raw Dataset for nnU-Net v2

#### ℹ️ About

This directory contains the original dataset modified according to the dataset format specified in [nnU-Net's documentation](https://github.com/MIC-DKFZ/nnUNet/blob/master/documentation/dataset_format.md). The `nnUNet_raw` folder can be used as-is for further nnU-Net preprocess inference, as it meets the desired folder structure and filename convention format.

The label images might appear completely black, but don’t worry—they’re not. Each pixel in the label images can have one of three values: 0, 1, or 2. Here, 0 represents the background, 1 denotes benign, and 2 indicates malignant. If you want to view the labels in a human-readable black-and-white format, please refer to the [original dataset](#original-dataset-combined-multi-masked-images).

The name of the dataset is `Breast`, whereas the ID is `101`. This information will be required for the nnUNet preprocess inference.

```bash
nnUNet_raw/
└── Dataset101_Breast/
    ├── imagesTr/  # Training images
    │   ├── breast_001_0000.png
    │   ├── breast_002_0000.png
    │   └── ...
    ├── labelsTr/  # Training segmentation masks
    │   ├── breast_001.png
    │   ├── breast_002.png
    │   └── ...
    └── dataset.json  # Dataset metadata
```

### Preprocessed Dataset

#### ℹ️ About

This directory contains the preprocessed dataset, where the nnU-Net preprocessing inference is applied to the raw dataset (nnUNet_raw). The `nnUNet_preprocessed` folder can be used as-is for further nnU-Net training inference on the `2d` configuration.

Note that the name of the dataset is `Breast`, whereas the ID is `101`. This information will be required for the nnUNet train inference.

```bash
nnUNet_preprocessed/
└── Dataset101_Breast/
    ├── dataset.json  # Metadata file used for training
    ├── dataset_fingerprint.json  # Dataset fingerprint
    ├── nnUNetPlans.json  # Training plans
    ├── splits_final.json  # Train/val/test split info
    ├── gt_segmentations/  # Ground truth segmentations
    │   ├── breast_001.png
    │   ├── breast_002.png
    │   └── ...
    └── nnUNetPlans_2d/  # Preprocessed data for training
        ├── breast_001.b2nd
        ├── breast_001.pkl
        ├── breast_001_seg.b2nd
        ├── breast_002.b2nd
        ├── breast_002.pkl
        ├── breast_002_seg.b2nd
        └── ...
```

---

## 🤝 Citation
If you use this dataset, please cite the original dataset:

📄 Al-Dhabyani W, Gomaa M, Khaled H, Fahmy A. Dataset of breast ultrasound images. Data in Brief. 2020 Feb;28:104863. DOI: 10.1016/j.dib.2019.104863.

---

## 👥 Contact
For questions or collaboration, reach out at:
- **Email:** ozdemirsoftware.dev@gmail.com
- **GitHub:** [veysel-ozdemir](https://github.com/veysel-ozdemir/)