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Congress: ECR25
Poster Number: C-12644
Type: Poster: EPOS Radiologist (scientific)
Authorblock: F. Schmitz1, H. Voigtländer1, H. Jang2, H-P. Schlemmer1, H-U. Kauczor1, S. Sedaghat1; 1Heidelberg/DE, 2Davis/US
Disclosures:
Fabian Schmitz: Nothing to disclose
Hendrik Voigtländer: Nothing to disclose
Hyungseok Jang: Nothing to disclose
Heinz-Peter Schlemmer: Nothing to disclose
Hans-Ulrich Kauczor: Nothing to disclose
Sam Sedaghat: Nothing to disclose
Keywords: Artificial Intelligence, Musculoskeletal soft tissue, Oncology, MR, Imaging sequences, Segmentation, Staging, Cancer
References

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[11]  L.H. Gimber, E.A. Montgomery, C.D. Morris, E.A. Krupinski, L.M. Fayad, MRI characteristics associated with high-grade myxoid liposarcoma, Clin Radiol 72(7) (2017) 613 e1-613 e6.

[12] Y.C.S. Ramon, M. Sese, C. Capdevila, T. Aasen, L. De Mattos-Arruda, S.J. Diaz-Cano, J. Hernandez-Losa, J. Castellvi, Clinical implications of intratumor heterogeneity: challenges and opportunities, J Mol Med (Berl) 98(2) (2020) 161-177.

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[14] L. Zhang, Z. Ren, Comparison of CT and MRI images for the prediction of soft-tissue sarcoma grading and lung metastasis via a convolutional neural networks model, Clin Radiol 75(1) (2020) 64-69.
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