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Tetteh, Giles; Navarro, Fernando; Meier, Raphael; Kaesmacher, Johannes; Paetzold, Johannes C; Kirschke, Jan S; Zimmer, Claus; Wiest, Roland; Menze, Bjoern H (2023). A deep learning approach to predict collateral flow in stroke patients using radiomic features from perfusion images. Frontiers in neurology, 14(1039693), p. 1039693. Frontiers Media S.A. 10.3389/fneur.2023.1039693
Xue, Song; Gafita, Andrei; Dong, Chao; Zhao, Yu; Tetteh, Giles; Menze, Bjoern H; Ziegler, Sibylle; Weber, Wolfgang; Afshar-Oromieh, Ali; Rominger, Axel; Eiber, Matthias; Shi, Kuangyu (2022). Application of machine learning to pretherapeutically estimate dosimetry in men with advanced prostate cancer treated with 177Lu-PSMA I&T therapy. European journal of nuclear medicine and molecular imaging, 49(12), pp. 4064-4072. Springer 10.1007/s00259-022-05883-w
Zhao, Yu; Gafita, Andrei; Vollnberg, Bernd; Tetteh, Giles; Haupt, Fabian; Afshar-Oromieh, Ali; Menze, Bjoern; Eiber, Matthias; Rominger, Axel; Shi, Kuangyu (2020). Deep neural network for automatic characterization of lesions on 68Ga-PSMA-11 PET/CT. European journal of nuclear medicine and molecular imaging, 47(3), pp. 603-613. Springer-Verlag 10.1007/s00259-019-04606-y
Zhao, Yu; Gafita, Andrei; Tetteh, Giles; Haupt, Fabian; Afshar Oromieh, Ali; Menze, Bjoern; Eiber, Matthias; Rominger, Axel; Shi, Kuangyu (2019). Deep Neural Network for Automatic Characterization of Lesions on 68Ga-PSMA PET/CT Images. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019, pp. 951-954. IEEE 10.1109/EMBC.2019.8857955
