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For: Shiri I, Akhavanallaf A, Sanaat A, Salimi Y, Askari D, Mansouri Z, Shayesteh SP, Hasanian M, Rezaei-Kalantari K, Salahshour A, Sandoughdaran S, Abdollahi H, Arabi H, Zaidi H. Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network. Eur Radiol 2021;31:1420-31. [PMID: 32879987 DOI: 10.1007/s00330-020-07225-6] [Cited by in Crossref: 17] [Cited by in F6Publishing: 7] [Article Influence: 8.5] [Reference Citation Analysis]
Number Citing Articles
1 Brogna B, Bignardi E, Brogna C, Volpe M, Lombardi G, Rosa A, Gagliardi G, Capasso PFM, Gravino E, Maio F, Pane F, Picariello V, Buono M, Colucci L, Musto LA. A Pictorial Review of the Role of Imaging in the Detection, Management, Histopathological Correlations, and Complications of COVID-19 Pneumonia. Diagnostics (Basel) 2021;11:437. [PMID: 33806423 DOI: 10.3390/diagnostics11030437] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 6.0] [Reference Citation Analysis]
2 Kulathilake KASH, Abdullah NA, Bandara AMRR, Lai KW. InNetGAN: Inception Network-Based Generative Adversarial Network for Denoising Low-Dose Computed Tomography. J Healthc Eng 2021;2021:9975762. [PMID: 34552709 DOI: 10.1155/2021/9975762] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Wang T, Chen Z, Shang Q, Ma C, Chen X, Xiao E. A Promising and Challenging Approach: Radiologists' Perspective on Deep Learning and Artificial Intelligence for Fighting COVID-19. Diagnostics (Basel) 2021;11:1924. [PMID: 34679622 DOI: 10.3390/diagnostics11101924] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Kulathilake KASH, Abdullah NA, Sabri AQM, Lai KW. A review on Deep Learning approaches for low-dose Computed Tomography restoration. Complex Intell Systems 2021;:1-33. [PMID: 34777967 DOI: 10.1007/s40747-021-00405-x] [Cited by in Crossref: 6] [Article Influence: 6.0] [Reference Citation Analysis]
5 Born J, Beymer D, Rajan D, Coy A, Mukherjee VV, Manica M, Prasanna P, Ballah D, Guindy M, Shaham D, Shah PL, Karteris E, Robertus JL, Gabrani M, Rosen-Zvi M. On the role of artificial intelligence in medical imaging of COVID-19. Patterns (N Y) 2021;2:100269. [PMID: 33969323 DOI: 10.1016/j.patter.2021.100269] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
6 Mohammadi R, Shokatian I, Salehi M, Arabi H, Shiri I, Zaidi H. Deep learning-based auto-segmentation of organs at risk in high-dose rate brachytherapy of cervical cancer. Radiotherapy and Oncology 2021;159:231-40. [DOI: 10.1016/j.radonc.2021.03.030] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 5.0] [Reference Citation Analysis]
7 Mishra S. Deep Transfer Learning-Based Framework for COVID-19 Diagnosis Using Chest CT Scans and Clinical Information. SN Comput Sci 2021;2:390. [PMID: 34337433 DOI: 10.1007/s42979-021-00785-4] [Reference Citation Analysis]
8 Sharma A, Balda S, Apreja M, Kataria K, Capalash N, Sharma P. COVID-19 Diagnosis: Current and Future Techniques. Int J Biol Macromol 2021:S0141-8130(21)02414-4. [PMID: 34774862 DOI: 10.1016/j.ijbiomac.2021.11.016] [Reference Citation Analysis]
9 Sanaat A, Shiri I, Ferdowsi S, Arabi H, Zaidi H. Robust-Deep: A Method for Increasing Brain Imaging Datasets to Improve Deep Learning Models' Performance and Robustness. J Digit Imaging 2022. [PMID: 35137305 DOI: 10.1007/s10278-021-00536-0] [Reference Citation Analysis]
10 Shiri I, Arabi H, Salimi Y, Sanaat A, Akhavanallaf A, Hajianfar G, Askari D, Moradi S, Mansouri Z, Pakbin M, Sandoughdaran S, Abdollahi H, Radmard AR, Rezaei-Kalantari K, Ghelich Oghli M, Zaidi H. COLI-Net: Deep learning-assisted fully automated COVID-19 lung and infection pneumonia lesion detection and segmentation from chest computed tomography images. Int J Imaging Syst Technol 2021. [PMID: 34898850 DOI: 10.1002/ima.22672] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
11 Bouchareb Y, Moradi Khaniabadi P, Al Kindi F, Al Dhuhli H, Shiri I, Zaidi H, Rahmim A. Artificial intelligence-driven assessment of radiological images for COVID-19. Comput Biol Med 2021;136:104665. [PMID: 34343890 DOI: 10.1016/j.compbiomed.2021.104665] [Reference Citation Analysis]
12 Rabiee B, Eibschutz LS, Asadollahi S, Gupta A, Akhlaghpoor S, Gholamrezanezhad A. The role of imaging techniques in understanding and evaluating the long-term pulmonary effects of COVID-19. Expert Rev Respir Med 2021;:1-13. [PMID: 34730039 DOI: 10.1080/17476348.2021.2001330] [Reference Citation Analysis]