CPCXR (COVID-19 Posteroanterior Chest X-Ray fused)

COVID-19 后前部胸部 X 射线融合 (CPCXR) 数据集是通过融合三个公开可用的数据集生成的：COVID-19 cxr 图像、北美放射学会 (RSNA) 和美国国家医学图书馆 (USNLM) 收集蒙哥马利国家 - NLM(MC)。该数据集由标记为 COVID-19、结核病、其他肺炎（SARS、MERS 等）和正常的疾病样本组成。该数据集可用于训练评估深度学习和机器学习模型作为二元和多类分类问题。

The COVID-19 Posteroanterior Chest X-ray Fusion (CPCXR) dataset is generated by fusing three publicly available datasets: COVID-19 CXR images, the RSNA chest X-ray dataset, and the Montgomery County dataset (MC) collected jointly by the Radiological Society of North America (RSNA) and the United States National Library of Medicine (USNLM). This dataset comprises disease samples annotated with four labels: COVID-19, tuberculosis, other pneumonia subtypes (e.g., SARS, MERS) and normal cases. It can be utilized to train and evaluate deep learning and machine learning models for both binary and multi-class classification tasks.

搜集汇总

背景与挑战

背景概述

CPCXR数据集是通过融合三个公开胸部X射线数据集生成的，包含COVID-19、结核病、其他肺炎和正常样本的标注。该数据集适用于训练和评估深度学习模型，用于二元或多类分类任务。