---
license: cc
dataset_info:
  features:
  - name: image
    dtype: image
  - name: annotation
    dtype: image
  - name: cancer_type
    dtype:
      class_label:
        names:
          '0': bening_breast_cancer
          '1': malignant_breast_cancer
  splits:
  - name: train
    num_bytes: 182212150.0
    num_examples: 547
  download_size: 181940841
  dataset_size: 182212150.0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# breastcanc-ultrasound-class

## Background

Cancer is the second leading cause of death worldwide, according to _IHME - Global Burden of Disease_, with 10.7 mln casualties in 2019. 

![total_deaths](./annual-number-of-deaths-by-cause.png)

Amongst the various types of cancer, a huge role is played by breast cancer, which stands in 4th position among the deadliest tumors, with more than 700.000 deaths during 2019 (_IHME - Global Burden of Disease_).

![death_composition](./total-cancer-deaths-by-type.png)

Moreover, breast cancer has the highest share of number of cases/100 people worldwide (0.23 cases/100 people; _IHME - Global Burden of Disease_), as shown in [table1](#table-1)
:

### Table 1

| Type of Cancer                       | Cases per 100 people                      |
|--------------------------------------|-------------------------------------------|
| Breast Cancer                        | 0.23                                     |
| Colon and Rectum Cancer              | 0.14                                      |
| Prostate cancer                      | 0.13                                      |
| Bladder Cancer                       | 0.034                                     |
| Stomach Cancer                       | 0.033                                     |

In this sense, it is more than vital to put intense effort into precision medicine and diagnostic tools for what concerns breast cancer: part of this effort should involve making curated dataset of diagnostic images available to the large public.

## Dataset source and composition

This dataset is part of the one kindly provided by [Walid Al-Dhabyani and collaborators in 2019](https://doi.org/10.1016/j.dib.2019.104863), and encompasses 547 images, 387 representing benign breast cancer ultrasound images and 160 of them representing malignant breast cancer ultrasound images, with their related masks.

## License, references and citation 

The dataset is hereby provided under CC family licenses. 

Please cite 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 when using it.