Breast Ultrasound Images Dataset (Dataset BUSI)

Dataset_BUSI.zip205.87MB
Type: Dataset
Tags:

Bibtex:
@article{,
title= {Breast Ultrasound Images Dataset (Dataset BUSI)},
keywords= {},
author= {},
abstract= {https://i.imgur.com/WV1Tfb7.png

| Subject area               | Medicine and Dentistry                                                                                                                                                             |
|----------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| More specific subject area | Radiology and Imaging                                                                                                                                                              |
| Type of data               | Images and mask images                                                                                                                                                             |
| How data was acquired      | LOGIQ E9 ultrasound and LOGIQ E9 Agile ultrasound system                                                                                                                           |
| Data format                | PNG                                                                                                                                                                                |
| Experimental factors       | All images are classified as normal, benign and malignant                                                                                                                          |
| Experimental features      | When medical images are used for training deep learning models, they provide fast and accurate results in classification, detection, and segmentation of breast cancer.            |
| Data source location       | Baheya Hospital for Early Detection & Treatment of Women's Cancer, Cairo, Egypt.                                                                                                   |
| Data accessibility         | https://scholar.cu.edu.eg/?q=afahmy/pages/dataset                                                                                                                                  |
| Related research article   | 1. Walid Al-Dhabyani, Mohammed Gomaa, Hussien Khaled and Aly Fahmy, Deep Learning Approaches for Data Augmentation and Classification of Breast Masses using Ultrasound Images [1] |



https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6906728/},
terms= {},
license= {},
superseded= {},
url= {https://scholar.cu.edu.eg/?q=afahmy/pages/dataset}
}

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