Deep learning model developed by multiparametric MRI in differential diagnosis of parotid gland tumors
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Medicine,Otorhinolaryngology
Link
https://link.springer.com/content/pdf/10.1007/s00405-022-07455-y.pdf
Reference25 articles.
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2. Liang YY, Xu F, Guo Y et al (2018) Diagnostic accuracy of magnetic resonance imaging techniques for parotid tumors, a systematic review and meta-analysis. Clin Imaging 52:36–43. https://doi.org/10.1016/j.clinimag.2018.05.026
3. Suzuki M, Kawata R, Higashino M et al (2019) Values of fine-needle aspiration cytology of parotid gland tumors: a review of 996 cases at a single institution. Head Neck 41:358–365. https://doi.org/10.1002/hed.25503
4. Tao X, Yang G, Wang P et al (2017) The value of combining conventional, diffusion-weighted and dynamic contrast-enhanced MR imaging for the diagnosis of parotid gland tumours. Dentomaxillofac Radiol 46:20160434. https://doi.org/10.1259/dmfr.20160434
5. Litjens G, Kooi T, Bejnordi BE et al (2017) A survey on deep learning in medical image analysis. Med Image Anal 42:60–88. https://doi.org/10.1016/j.media.2017.07.005
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