遇见数据集

HCFMRP COVID-19 & LID (v1)

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NIAID Data Ecosystem2026-03-13 收录
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Dataset designed to characterize lung interstitial diseases (LID) and COVID-19 on chest X-ray. For the composition of the dataset, frontal chest X-ray of patients from the Ribeirão Preto Medical School of University of São Paulo (Brazil) were classified into three groups: healthy (382 images), with LID (308 images), and with COVID-19 (189 images). All images were analyzed by a thoracic radiologist and COVID-19 diagnosis was confirmed by RT-PCR. For each of the groups, three types of files are available, all anonymized: the frontal view of the chest X-ray in DICOM format; the original images converted to PNG format; and the same images in 3-channel PNG format (RGB). The following directory and file structure is presented: 1-Normal: for healthy cases normal-dcm-anonymized: anonymized DICOM files normal-png: image files converted to PNG normal-png-RGB: image files converted to 3-channel PNG 2-LID: for LID cases lid-dcm-anonymized: anonymized DICOM files lid-png: image files converted to PNG lid-png-RGB: image files converted to 3-channel PNG 3-COVID: for COVID-19 cases covid-dcm-anonymized: anonymized DICOM files covid-png: image files converted to PNG covid-png-RGB: image files converted to 3-channel PNG For more information, contact us: https://mainlab.fmrp.usp.br/

创建时间:
2022-07-16
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