该内容是由用户自发提供,聚数力平台仅提供平台,让大数据应用过程中的信息实现共享、交易与托管。如该内容涉及到您的隐私或可能侵犯版权,请告知我们及时删除。
数据集概述
https://academictorrents.com/details/d0b7b7ae40610bbeaea385aeb51658f527c86a16
Tags:Abstract:
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/
URL: https://scholar.cu.edu.eg/?q=afahmy/pages/dataset
License:
No license specified, the work may be protected by copyright.
数据集详情
暂无
数据集元数据
暂无
概念层次
领域场景: | 未指定 |
领域问题: | 未指定 |
领域应用: | 未指定 |
应用案例: | 未指定 |