UIdataGB Gallblader Diseases Dataset

@article{,
title= {UIdataGB Gallblader Diseases Dataset},
keywords= {machine learning, deep learning, Medical imaging, Gallbladder diseases, gallbladder ultrasound, gallbladder diseases dataset, UIdataGB, cholecystitis ultrasound, gallstones classification},
author= {},
abstract= {The dataset is composed of ultrasound images of the GB organ from inside the gastrointestinal tract. The dataset includes 9 classes according to anatomical landmarks. Each class represents a GB disease.

Published: 23 January 2024 | Version 1 | DOI: 10.17632/r6h24d2d3y.1 


Turki, Amina; Mahdi Obaid, Ahmed; Bellaaj, Hatem; Ksantini, Mohamed; Altaee, Abdulla (2024), “Gallblader Diseases Dataset  ”, Mendeley Data, V1, doi: 10.17632/r6h24d2d3y.1

"The UIdataGB dataset consists of 10692 images, annotated, and verified by medical doctorsand experienced radiologists. It includes 9 classes according to anatomical landmarks. Each classcontains nearly 1200 images. Therefore, the dataset is balanced in terms of diseases. In total,1782 patients were involved in the data collection; the number of female images was 6246,with an average age of 63.4, while the number of male images was 4446, with an average ageof 59.6.The number of images is sufficient to be used for different tasks, e.g., image retrieval, ML, DL,and transfer learning (TL), etc. The anatomical landmark of the GB determines the pathologicalfinding like cholecystitis, stone of the GB and polyps.The dataset consists of images with a resolution of 90 0×120 0 pixels and they are sorted intoseparate nine folders named according to the content. Tables 1 and 2 show the distribution ofdiseases in terms of images and patients’ numbers as well as the distribution of images accord-ing to gender."



https://www.sciencedirect.com/science/article/pii/S2352340924003950},
terms= {},
license= {https://creativecommons.org/licenses/by/4.0/},
superseded= {},
url= {https://data.mendeley.com/datasets/r6h24d2d3y/1}
}