COVID-ARC



COVID-ARC Dataset CitationsSite 01: Soares, Eduardo, Angelov, Plamen, Biaso, Sarah, Higa Froes, Michele, and Kanda Abe, Daniel. "SARS-CoV-2 CT-scan dataset: A large dataset of real patients CT scans for SARS-CoV-2 identification." medRxiv (2020). doi: 02:Zhao, Jinyu and Zhang, Yichen and He, Xuehai and Xie, Pengtao. “COVID-CT-Dataset: a CT scan dataset about COVID-19.” arXiv preprint arXiv:2003.13865 (2020). Site 03:MedSeg, H. B. Jenssenand T. Sakinis, “MedSeg Covid Dataset 1”. figshare, 05-Jan-2021, doi: 10.6084/m9.figshare.13521488.v2. Site 04:Data Sources:[1] - Paiva, O., 2020. - Helping Radiologists To Help People In More Than 100 Countries! | Coronavirus Cases - 冠状病毒病例. [online] . Available at: <link> [Accessed 20 March 2020].[2] - Glick, Y., 2020. Viewing Playlist: COVID-19 Pneumonia | . [online] . Available at: <link> [Accessed 20 April 2020].Annotations:[3] - Ma Jun, Ge Cheng, Wang Yixin, An Xingle, Gao Jiantao, Yu Ziqi, … He Jian. (2020). COVID-19 CT Lung and Infection Segmentation Dataset (Version Verson 1.0) [Data set]. Zenodo. DOISite 05: De La Iglesia Vayá, Maria, Jose Manuel Saborit, Joaquim Angel Montell, Antonio Pertusa, Aurelia Bustos, Miguel Cazorla, Joaquin Galant et al. "Bimcv covid-19+: a large annotated dataset of rx and ct images from covid-19 patients." arXiv preprint arXiv:2006.01174 (2020).Site 06: Morozov, S.P., Andreychenko, A.E., Pavlov, N.A., Vladzymyrskyy, A.V., Ledikhova, N.V., Gombolevskiy, V.A., Blokhin, I.A., Gelezhe, P.B., Gonchar, A.V. and Chernina, V.Y., 2020. MosMedData: Chest CT Scans With COVID-19 Related Findings Dataset. arXiv preprint arXiv:2005.06465. Site 07: Mohammad Rahimzadeh, Abolfazl Attar, Seyed Mohammad Sakhaei, A Fully Automated Deep Learning-based Network For Detecting COVID-19 from a New And Large Lung CT Scan Dataset, Biomedical Signal Processing and Control, 2021, 102588, ISSN 1746-8094, 08: COVID-19 Image Data Collection: Prospective Predictions Are the FutureJoseph Paul Cohen and Paul Morrison and Lan Dao and Karsten Roth and Tim Q Duong and Marzyeh Ghassemi, arXiv:2006.11988, , 2020Site 09: Guotai Wang, Xinglong Liu, Chaoping Li, Zhiyong Xu, Jiugen Ruan, Haifeng Zhu, Tao Meng, Kang Li, Ning Huang, Shaoting Zhang. “A Noise-robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesions from CT Images.” IEEE Transactions on Medical Imaging, 39, no. 8(2020): 2653 - 2663.. Site 10: Zhang, Kang, Xiaohong Liu, Jun Shen, Zhihuan Li, Ye Sang, Xingwang Wu, Yunfei Zha et al. "Clinically applicable AI system for accurate diagnosis, quantitative measurements, and prognosis of COVID-19 pneumonia using computed tomography." Cell 181, no. 6 (2020): 1423-1433.Site 11: Winther, Hinrich B.; Laser, Hans; Gerbel, Svetlana; Maschke, Sabine K.; B. Hinrichs, Jan; Vogel-Claussen, Jens; et al. (2020): COVID-19 Image Repository. figshare. Dataset. Site 12: [1] - M.E.H. Chowdhury, T. Rahman, A. Khandakar, R. Mazhar, M.A. Kadir, Z.B. Mahbub, K.R. Islam, M.S. Khan, A. Iqbal, N. Al-Emadi, M.B.I. Reaz, M. T. Islam, “Can AI help in screening Viral and COVID-19 pneumonia?” IEEE Access, Vol. 8, 2020, pp. 132665 - 132676. Paper link[2] - Rahman, T., Khandakar, A., Qiblawey, Y., Tahir, A., Kiranyaz, S., Kashem, S.B.A., Islam, M.T., Maadeed, S.A., Zughaier, S.M., Khan, M.S. and Chowdhury, M.E., 2020. Exploring the Effect of Image Enhancement Techniques on COVID-19 Detection using Chest X-ray Images. Paper LinkSite 13: Site 14: Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Inf Dis. 20(5):533-534. doi: 10.1016/S1473-3099(20)30120-1"Site 15: Kim, J., Jang, S., Lee, W., Lee, J. K., & Jang, D. H. DS4C Patient Policy Province Dataset: a Comprehensive COVID-19 Dataset for Causal and Epidemiological Analysis.Site 16: Born, J., Wiedemann, N., Cossio, M., Buhre, C., Br?ndle, G., Leidermann, K., Aujayeb, A., Moor, M., Rieck, B. and Borgwardt, K., 2021. Accelerating Detection of Lung Pathologies with Explainable Ultrasound Image Analysis. Applied Sciences, 11(2), p.672.Born, J., N. Weidemann, M. Cossio, C. Buhre, G. Br?ndle, K. Leidermann, A. Aujayeb, B. Rieck, and K. Borgwardt. "L2 Accelerating COVID-19 differential diagnosis with explainable ultrasound image analysis: an AI tool." (2021): A230-A231.Site 17:An P, Xu S, Harmon SA, Turkbey EB, Sanford TH, Amalou A, Kassin M, Varble N, Blain M, Anderson V, Patella F, Carrafiello G, Turkbey BT, Wood BJ (2020). CT Images in Covid-19 [Data set]. The Cancer Imaging Archive. DOI: 18:Desai, S., Baghal, A., Wongsurawat, T., Al-Shukri, S., Gates, K., Farmer, P., Rutherford, M., Blake, G.D., Nolan, T., Powell, T., Sexton, K., Bennett, W., Prior, F. (2020). Data from Chest Imaging with Clinical and Genomic Correlates Representing a Rural COVID-19 Positive Population [Data set]. The Cancer Imaging Archive. DOI: 19: Tsai, E., Simpson, S., Lungren, M.P., Hershman, M., Roshkovan, L., Colak, E., Erickson, B.J., Shih, G., Stein, A., Kalpathy-Cramer, J., Shen, J., Hafez, M.A.F., John, S., Rajiah, P., Pogatchnik, B.P., Mongan, J.T., Altinmakas, E., Ranschaert, E., Kitamura, F.C., Topff, L., Moy, L., Kanne, J.P., & Wu, C. (2020). Data from the Medical Imaging Data Resource Center - RSNA International COVID Radiology Database Release 1a - Chest CT Covid+ (MIDRC-RICORD-1a). Data from The Cancer Imaging Archive (2020). DOI: 20:Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, MohammadhadiBagheri, Ronald M. Summers.ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases, IEEE CVPR, pp. 3462-3471,2017Site 21:Kermany, Daniel; Zhang, Kang; Goldbaum, Michael (2018), “Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images for Classification”, Mendeley Data, V2, doi: 10.17632/rscbjbr9sj.2Site 22: Site 23: Altschul, David (2021), Neurologic complications of COVID-19, Dryad, Dataset, 24: Wang, G., Liu, X., Shen, J. et al. A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images. Nat Biomed Eng (2021). 25:“Zaffino P, Marzullo A, Moccia S, Calimeri F, De Momi E, Bertucci B, Arcuri PP, Spadea MF.An Open-Source COVID-19 CT Dataset with Automatic Lung Tissue Classification for Radiomics.Bioengineering. 2021; 8(2):26“.Site 26: Khan, Ali Haider; Hussain, Muzammil (2020), “ECG Images dataset of Cardiac and COVID-19 Patients”, Mendeley Data, V1, doi: 10.17632/gwbz3fsgp8.1Site 27:Hurt, B., Rubel, M., Masutani, E., Jacobs, K., Hahn, L., Horowitz, M., Kligerman, S.,?Hsiao, A., Radiologist-Supervised Transfer Learning – Improving X-Ray Localization of Pneumonia and Prognostication of Patients with COVID-19, J Thoracic Imaging (in press) ................
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