CT Images in COVID-19

This retrospective NIfTI image dataset consists of unenhanced chest CTs from 632 patients with COVID-19 infections. The images were acquired at the point of care in an outbreak setting from patients with Reverse Transcription Polymerase Chain Reaction (RT-PCR) confirmation for the presence of SARS-CoV-2.
Patients presented to a health care setting with a combination of symptoms, exposure to an infected patient, or travel history to an outbreak region. All patients had a positive RT-PCR for SARS-CoV-2 from a sample obtained within 1 day of the initial CT. CT exams were performed with intravenous contrast and a soft tissue reconstruction algorithm. The DICOM images were subsequently converted into NIfTI format.

A multidisciplinary team trained several models using portions of this TCIA data set, along with additional CTs and manually annotated images from other sources. A classification model derived in part from this data is described at: https://doi.org/10.1038/s41467-020-17971-2. The NVIDIA-related frameworks and models specific to this publication are available at no cost as part of the NVIDIA Clara Train SDK at https://ngc.nvidia.com/catalog/containers/nvidia:clara:ai-covid-19. This includes both inference-based pipelines for evaluation, as well as model weights for further training or fine tuning in outside institutions. In addition, a web-based version of this model (for research use only) with drag-and-drop functionality for evaluating individual scans can be found at https://marketplace.arterys.com/model/nvidiacovidCT. Uploading a CT yields a return email that contains results.

本回顾性NIfTI影像数据集包含632例新型冠状病毒肺炎（COVID-19）患者的非增强胸部CT影像。该数据集影像采集于疫情暴发场景下的临床照护场景，受试者均经逆转录聚合酶链反应(Reverse Transcription Polymerase Chain Reaction, RT-PCR)确认感染严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)。受试者均因出现多种症状、接触过感染者或有疫情暴发地区旅居史前往医疗机构就诊。所有受试者在首次CT检查前1天内采集的样本经RT-PCR检测均呈SARS-CoV-2阳性。CT检查均采用静脉注射对比剂及软组织重建算法完成。后续将所有DICOM影像转换为NIfTI格式。

多学科团队利用该TCIA数据集的部分样本、额外CT影像以及其他来源的手动标注影像训练了多款模型。基于该数据集部分样本构建的分类模型相关信息可参见：https://doi.org/10.1038/s41467-020-17971-2。本论文专属的英伟达(NVIDIA)相关框架与模型可通过英伟达克拉拉训练软件开发工具包(NVIDIA Clara Train SDK)免费获取，获取地址为：https://ngc.nvidia.com/catalog/containers/nvidia:clara:ai-covid-19。该资源包含用于评估的基于推理的流水线，以及可供外部机构开展进一步训练或微调的模型权重文件。此外，该模型的网页版（仅用于科研）支持拖拽式上传单份扫描影像以完成评估，访问地址为：https://marketplace.arterys.com/model/nvidiacovidCT。上传CT影像后，系统将通过邮件返回检测结果。

搜集汇总

背景与挑战

背景概述

该数据集是一个包含632名COVID-19感染患者未增强胸部CT图像的NIfTI格式数据集，所有患者均在CT后1天内通过RT-PCR确认感染SARS-CoV-2。图像采集于疫情爆发环境，使用静脉对比剂和软组织重建算法，并已从DICOM转换为NIfTI格式，适用于COVID-19相关研究和模型训练。