TITLE: A High-Resolution Chest CT-Scan Image Dataset for COVID-19 Diagnosis and Differentiation 

ABSTRACT: During the COVID-19 pandemic, computed tomography (CT) is a good way to
diagnose COVID-19 patients. HRCT (High-Resolution Computed Tomography) is a
form of computed tomography that uses advanced methods to improve image
resolution. Publicly accessible COVID-19 CT image datasets are very difficult
to come by due to privacy concerns, which impedes the study and development of
AI-powered COVID-19 diagnostic algorithms based on CT images. To address this
problem, we have introduced HRCTv1-COVID-19, a new COVID-19 high resolution
chest CT Scan image dataset that includes not only COVID-19 cases of Ground
Glass Opacity (GGO), Crazy Paving, and Air Space Consolidation, but also CT
images of cases with negative COVID-19. The HRCTv1-COVID-19 dataset, which
includes slice-level, and patient-level labels, has the potential to aid
COVID-19 research, especially for diagnosis and differentiation using
artificial intelligence algorithms, machine learning and deep learning methods.
This dataset is accessible through web at: http://databiox.com and includes
181,106 chest HRCT images from 395 patients with four labels: GGO, Crazy
Paving, Air Space Consolidation and Negative.
  Keywords- Dataset, COVID-19, CT-Scan, Computed Tomography, Medical Imaging,
Chest Image.
During the COVID-19 pandemic, computed tomography (CT) is a good way to
diagnose COVID-19 patients. HRCT (High-Resolution Computed Tomography) is a
form of computed tomography that uses advanced methods to improve image
resolution. Publicly accessible COVID-19 CT image datasets are very difficult
to come by due to privacy concerns, which impedes the study and development of
AI-powered COVID-19 diagnostic algorithms based on CT images. To address this
problem, we have introduced HRCTv1-COVID-19, a new COVID-19 high resolution
chest CT Scan image dataset that includes not only COVID-19 cases of Ground
Glass Opacity (GGO), Crazy Paving, and Air Space Consolidation, but also CT
images of cases with negative COVID-19. The HRCTv1-COVID-19 dataset, which
includes slice-level, and patient-level labels, has the potential to aid
COVID-19 research, especially for diagnosis and differentiation using
artificial intelligence algorithms, machine learning and deep learning methods.
This dataset is accessible through web at: http://databiox.com and includes
181,106 chest HRCT images from 395 patients with four labels: GGO, Crazy
Paving, Air Space Consolidation and Negative.
  Keywords- Dataset, COVID-19, CT-Scan, Computed Tomography, Medical Imaging,
Chest Image.
A High-Resolution Chest CT-Scan Image Dataset for COVID-19 Diagnosis and Differentiation
http://arxiv.org/abs/2205.03408v1