Here are links to cited references to further explore the topics proposed in our newsletters.
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Laghi A, Tamburi V, Polici M et al. Management decisions of an Academic Radiology Department during COVID-19 pandemic: the important support of a business analytics software. Eur Radiol. 2022 Oct;32(10):7048-7055.
LinkSammer MBK, Stahl A, Ozkan E, Sher AC. Implementation of a software distribution intervention to improve workload balance in an Academic Pediatric Radiology Department. J Digit Imaging. 2021 Jun;34(3):741-749.
LinkShimada Y, Kudo Y, Maehara S et al. Artificial intelligence-based radiomics for the prediction of nodal metastasis in early-stage lung cancer. Sci Rep. 2023 Jan 19;13(1):1028.
LinkChassagnon G, De Margerie-Mellon C, Vakalopoulou M et al. Artificial intelligence in lung cancer: current applications and perspectives. Jpn J Radiol. 2023 Mar;41(3):235-244.
LinkFlor N, Pickhardt PJ, Maconi G et al. CT colonography followed by elective surgery in patients with acute diverticulitis: a radiological-pathological correlation study. Abdom Radiol (NY). 2021 Feb;46(2):491-497.
LinkWesp P, Grosu S, Graser A et al. Deep learning in CT colonography: differentiating premalignant from benign colorectal polyps. Eur Radiol. 2022 Jul;32(7):4749-4759.
LinkTan M, Low HM, Shelat V, Tan CH. Imaging patterns in non-traumatic spleen lesions in adults-a review. Jpn J Radiol. 2022 Jul;40(7):664-677.
LinkZhang M, Gu S, Yuhui S. The use of deep learning methods in low-dose computed tomography image reconstruction: a systematic review. Complex Intell Syst. 2022;8:5545-5561.
LinkSato M, Ichikawa Y, Domae K et al. Deep learning image reconstruction for improving image quality of contrast-enhanced dual-energy CT in abdomen. Eur Radiol. 2022 Aug;32(8):5499-5507.
LinkGriffin LM. Computed tomography for aortic assessment in children. Pediatr Radiol. 2022 Dec;52(13):2470-2484.
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