Tuberculosis (TB) Chest X-ray Database

A team of researchers from Qatar University, Doha, Qatar, and the University of Dhaka, Bangladesh along with their collaborators from Malaysia in collaboration with medical doctors from Hamad Medical Corporation and Bangladesh have created a database of chest X-ray images for Tuberculosis (TB) positive cases along with Normal images. In our current release, there are 3500 TB images, and 3500 normal images.Note: The research team managed to classify TB and Normal Chest X-ray images with an accuracy of 98.3%. This scholarly work is published in IEEE Access Link. Please make sure you give credit to us while using the dataset, code, and trained models.Credit should go to the following:Tawsifur Rahman, Amith Khandakar, Muhammad A. Kadir, Khandaker R. Islam, Khandaker F. Islam, Zaid B. Mahbub, Mohamed Arselene Ayari, Muhammad E. H. Chowdhury. "Reliable Tuberculosis Detection using Chest X-ray with Deep Learning, Segmentation and Visualization". [Accepted: IEEE Access] [https://arxiv.org/ftp/arxiv/papers/2007/2007.14895.pdf]

来自卡塔尔国多哈市卡塔尔大学、孟加拉国达卡大学的研究团队，联合马来西亚合作方，并与哈马德医疗公司及孟加拉国的医务医师开展合作，构建了一套针对结核病（Tuberculosis, TB）阳性病例与正常胸部X光影像的数据集。
本次发布的数据集包含3500张结核阳性影像与3500张正常胸部X光影像。
注：该研究团队已实现结核与正常胸部X光影像分类的准确率达98.3%。本学术成果已发表于《IEEE Access》期刊。使用本数据集、代码及训练好的模型时，请务必注明本研究贡献。相关贡献应归于以下作者：Tawsifur Rahman、Amith Khandakar、Muhammad A. Kadir、Khandaker R. Islam、Khandaker F. Islam、Zaid B. Mahbub、Mohamed Arselene Ayari、Muhammad E. H. Chowdhury。
论文题为《基于深度学习、分割与可视化的胸部X光影像结核可靠检测（Reliable Tuberculosis Detection using Chest X-ray with Deep Learning, Segmentation and Visualization）》，已被《IEEE Access》收录，预印本链接：https://arxiv.org/ftp/arxiv/papers/2007/2007.14895.pdf。

搜集汇总

背景与挑战

背景概述

该数据集是一个用于结核病检测的胸部X光图像数据库，包含7000张图像（结核病阳性和正常图像各3500张）。数据集由多国研究团队合作创建，并已在IEEE Access发表相关研究，其基于深度学习的分类准确率达到98.3%，适用于医疗影像分析和人工智能辅助诊断研究。