ISSN:2167-7964
Journal of Radiology
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黑料网 Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers
Citations : 551
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Journal of Radiology : Citations & Metrics Report
Articles published in Journal of Radiology have been cited by esteemed scholars and scientists all around the world. Journal of Radiology has got h-index 10, which means every article in Journal of Radiology has got 10 average citations.
Following are the list of articles that have cited the articles published in Journal of Radiology.
| 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | |
|---|---|---|---|---|---|---|---|---|---|
Total published articles |
91 | 97 | 60 | 60 | 21 | 15 | 19 | 44 | 41 |
Research, Review articles and Editorials |
34 | 56 | 20 | 19 | 17 | 8 | 0 | 0 | 0 |
Research communications, Review communications, Editorial communications, Case reports and Commentary |
46 | 5 | 2 | 11 | 4 | 1 | 0 | 0 | 0 |
Conference proceedings |
0 | 0 | 5 | 0 | 0 | 0 | 42 | 88 | 35 |
Citations received as per Google Scholar, other indexing platforms and portals |
46 | 48 | 90 | 86 | 74 | 78 | 108 | 103 | 101 |
| Journal total citations count | 551 |
| Journal impact factor | 2.99 |
| Journal 5 years impact factor | 4.66 |
| Journal cite score | 4.52 |
| Journal h-index | 10 |
| Journal h-index since 2019 | 10 |
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Wulansari, D. P., & Azhari, A. (2021). Biomarker of buccal mucosa cells damaged after exposure to panoramic radiography: a literature review. Jurnal Radiologi Dentomaksilofasial Indonesia (JRDI), 5(1), 27-30. |
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Santos, F. A., Santos, W. S., Galeano, D. C., Cavalcante, F. R., Silva, A. X., Souza, S. O., & J脙潞nior, A. B. C. (2017). Cancer risk coefficient for patient undergoing kyphoplasty surgery using Monte Carlo method. Radiation Physics and Chemistry, 140, 423-427. |
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Santos, W. S., Neves, L. P., Perini, A. P., Caldas, L. V., & Maia, A. F. (2014). Coefficients calculations of conversion of cancer risk for occupational exposure using Monte Carlo simulations in cardiac procedures of interventionist radiology. |
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Ghany, H. A., Diab, H. M., Salah, A., & Taha, A. A. (2020). Senior interventional cardiologists are exposed to higher effective doses than other staff members. Radiation and Environmental Biophysics, 59(4), 743-748. |
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Santos, W. S., Neves, L. P., Perini, A. P., Belinato, W., Caldas, L. V., Carvalho Jr, A. B., & Maia, A. F. (2015). Exposures in interventional radiology using Monte Carlo simulation coupled with virtual anthropomorphic phantoms. Physica Medica, 31(8), 929-933. |
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Le Coultre, R., Bize, J., Champendal, M., Wittwer, D., Ryckx, N., Aroua, A., ... & Verdun, F. R. (2016). Exposure of the Swiss population by radiodiagnostics: 2013 review. Radiation protection dosimetry, 169(1-4), 221-224. |
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Yamada, A. Compartment model analysis of intravenous contrast-enhanced dynamic. |
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Simeth, J., & Cao, Y. (2020). GAN and dual?input two?compartment model?based training of a neural network for robust quantification of contrast uptake rate in gadoxetic acid?enhanced MRI. Medical physics, 47(4), 1702-1712. |
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Komatsu, D., Yamada, A., Suzuki, T., Kurozumi, M., Fujinaga, Y., Ueda, K., & Kadoya, M. (2018). Compartment model analysis of intravenous contrast?enhanced dynamic computed tomography in hepatic hemodynamics: A validation study using intra?arterial contrast?enhanced computed tomography. Hepatology Research, 48(10), 829-838. |
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Simeth, J., Johansson, A., Owen, D., Cuneo, K., Mierzwa, M., Feng, M., ... & Cao, Y. (2018). Quantification of liver function by linearization of a two?compartment model of gadoxetic acid uptake using dynamic contrast?enhanced magnetic resonance imaging. NMR in Biomedicine, 31(6), e3913. |
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Zhang, Y., Liu, Y., Sun, B., Zhang, X., & Jiang, X. (2015). Practical design of multi?channel MOSFET RF transmission system for 7 T animal MR imaging. Concepts in Magnetic Resonance Part B: Magnetic Resonance Engineering, 45(4), 191-200. |
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Pang, Y., Wong, E. W., Yu, B., & Zhang, X. (2014). Design and numerical evaluation of a volume coil array for parallel MR imaging at ultrahigh fields. Quantitative imaging in medicine and surgery, 4(1), 50. |
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P脙漏rez, J. M., Barqu脙颅n, P. G., Marcos, A. V., Bolao, J. G., & Alema脙卤, G. B. (2016). Complicaciones asociadas a la ablaci脙鲁n mediante radiofrecuencia de venas pulmonares. Radiolog脙颅a, 58(6), 444-453. |
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Ghasemi, M. A. H. D. I. E. H. (2018). Low and High Frequency Band Connectivity in the Base Fluctuations of the Brain using fMRI Data of Parkinson Disease. Iranian Journal of Biomedical Engineering, 12(1), 51-61. |
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Naseri, P., Majd, H. A., Tabatabaei, S. M., Khadembashi, N., Najibi, S. M., & Nazari, A. (2021). Functional brain response to emotional musical stimuli in depression, using INLA approach for approximate Bayesian inference. Basic and Clinical Neuroscience, 12(1), 95. |
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Nazari, A., Alavimajd, H., Shakeri, N., Bakhshandeh, M., Faghihzadeh, E., & Marzbani, H. (2019). Prediction of brain connectivity map in resting-state fmri data using shrinkage estimator. Basic and clinical neuroscience, 10(2), 147. |
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Behroozi, M., & Daliri, M. R. (2014). Predicting brain states associated with object categories from fMRI data. Journal of integrative neuroscience, 13(04), 645-667. |
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Behroozi, M., & Daliri, M. R. (2015). RDLPFC area of the brain encodes sentence polarity: a study using fMRI. Brain imaging and behavior, 9(2), 178-189. |
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Daliri, M. R., & Behroozi, M. (2013). Advantages and disadvantages of resting state functional connectivity magnetic resonance imaging for clinical applications. OMICS Journal of Radiology, 3(1), 1-2. |
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Behroozi, M., & Daliri, M. R. (2012). Software tools for the analysis of functional magnetic resonance imaging. Basic and Clinical Neuroscience, 3(5), 71-83. |
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