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Datasets/Large COVID-19 CT scan slice dataset

Large COVID-19 CT scan slice dataset

ImagesIntroduced 2021-05-22

"We built a large lung CT scan dataset for COVID-19 by curating data from 7 public datasets listed in the acknowledgements. These datasets have been publicly used in COVID-19 diagnosis literature and proven their efficiency in deep learning applications. Therefore, the merged dataset is expected to improve the generalization ability of deep learning methods by learning from all these resources together.

These datasets are made available in different formats. Our goal is to provide a large dataset of COVID-19, Normal, and CAP CT slices together with their corresponding metadata. Some of the datasets consist of categorized CT slices, and some include CT volumes with annotated lesion slices. Therefore, we used the slice-level annotations to extract axial slices from CT volumes. We then converted all the images to 8-bit to have a consistent depth.

To ensure the dataset quality, we have removed the closed lung normal slices that do not carry information about inside lung manifestations. Additionally, we did not include images lacking clear class labels or patient information. In total, we have gathered 7,593 COVID-19 images from 466 patients, 6,893 normal images from 604 patients, and 2,618 CAP images from 60 patients. All of our CAP images are from Afshar et al. dataset, in which 25 cases are already annotated. Our radiologist has annotated the remaining 35 CT scan volumes. This is the largest COVID-19 lung CT dataset so far, to the best of our knowledge." - Source: A Robust Ensemble-Deep Learning Model for COVID-19 Diagnosis based on an Integrated CT Scan Images Database

Acknowledgements

  • J. Zhao, Y. Zhang, X. He, and P. Xie, "COVID-CT-Dataset: a CT scan dataset about COVID-19," arXiv preprint arXiv:2003.13865, 2020.

  • P. Afshar et al., "COVID-CT-MD: COVID-19 Computed Tomography (CT) Scan Dataset Applicable in Machine Learning and Deep Learning," arXiv preprint arXiv:2009.14623, 2020.

  • J. P. Cohen, P. Morrison, L. Dao, K. Roth, T. Q. Duong, and M. Ghassemi, "Covid-19 image data collection: Prospective predictions are the future," arXiv preprint arXiv:2006.11988, 2020.

  • S. Morozov et al., "MosMedData: Chest CT Scans With COVID-19 Related Findings Dataset," arXiv preprint arXiv:2005.06465, 2020.

  • M. Rahimzadeh, A. Attar, and S. M. Sakhaei, "A Fully Automated Deep Learning-based Network For Detecting COVID-19 from a New And Large Lung CT Scan Dataset," medRxiv, 2020.

  • M. Jun et al., "COVID-19 CT Lung and Infection Segmentation Dataset," Zenodo, Apr, vol. 20, 2020.

  • "COVID-19." 2020. [Online] http://medicalsegmentation.com/covid19/ [Accessed 23 December, 2020].

Benchmarks

COVID-19 Diagnosis/AUC-ROCCOVID-19 Diagnosis/AccuracyCOVID-19 Diagnosis/Macro F1COVID-19 Diagnosis/Macro PrecisionCOVID-19 Diagnosis/Macro RecallCOVID-19 Diagnosis/Micro PrecisionCOVID-19 Diagnosis/SpecificityFew-Shot Learning/AUC-ROCFew-Shot Learning/Accuracy Few-Shot Learning/Macro F1Few-Shot Learning/Macro PrecisionFew-Shot Learning/Macro RecallFew-Shot Learning/Micro PrecisionFew-Shot Learning/SpecificityMeta-Learning/AUC-ROCMeta-Learning/Accuracy Meta-Learning/Macro F1Meta-Learning/Macro PrecisionMeta-Learning/Macro RecallMeta-Learning/Micro PrecisionMeta-Learning/Specificity

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COVID-19 DiagnosisClassificationComputed Tomography (CT)Few-Shot LearningMeta-Learning