Review — BUSI: Dataset of Breast Ultrasound Images
Dataset of Breast Ultrasound Images,
BUSI, by Cairo University
2020 JDataInBrief, Over 270 Citations (Sik-Ho Tsang @ Medium)
Medical Image Analysis, Medical Imaging, Image Segmentation
- The dataset consists of the medical images of breast cancer using ultrasound scan, which is categorized into three classes: normal, benign, and malignant images.
- Breast ultrasound images can produce great results in classification, detection, and segmentation of breast cancer when combined with machine learning.
- Access: https://scholar.cu.edu.eg/?q=afahmy/pages/dataset
1. BUSI Dataset
- Ultrasound (US) images are generally in grayscale.
- At the beginning, the number of images collected was 1100. After performing preprocessing to the dataset, the number of images was reduced to 780 images.
- LOGIQ E9 ultrasound system and LOGIQ E9 Agile ultrasound system produce image resolution of 1280×1024.
- All images were cropped. The average image size of 500×500 pixels.
- The image annotation is added to the image name.
- A freehand segmentation is established for each image separately.