1. Bilic, P., Christ, P. F., Vorontsov, E., Chlebus, G., Chen, H., Dou, Q., Fu, C.-W., Han, X., Heng, P.-A., Hesser, J., Kadoury, S., Konopczynski, T., Le, M., Li, C., Li, X., Lipkovà, J., Lowengrub, J., Meine, H., Moltz, J. H., Pal, C., Piraud, M., Qi, X., Qi, J., Rempfler, M., Roth, K., Schenk, A., Sekuboyina, A., Vorontsov, E., Zhou, P., Hülsemeyer, C., Beetz, M., Ettlinger, F., Gruen, F., Kaissis, G., Lohöfer, F., Braren, R., Holch, J., Hofmann, F., Sommer, W., Heinemann, V., Jacobs, C., Mamani, G. E. H., van Ginneken, B., Chartrand, G., Tang, A., Drozdzal, M., Ben-Cohen, A., Klang, E., Amitai, M. M., Konen, E., Greenspan, H., Moreau, J., Hostettler, A., Soler, L., Vivanti, R., Szeskin, A., Lev-Cohain, N., Sosna, J., Joskowicz, L., Menze, B. H., 2019. The liver tumor segmentation benchmark (LiTS). arXiv:1901.04056 [cs]
2. Bochkovskiy, A., Wang, C.-Y., Liao, H.-Y. M., 2020. YOLOv4: optimal speed and accuracy of object detection. arXiv:2004.10934 [cs, eess].
3. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries;Bray;CA Cancer J. Clin.,2018
4. Computed tomography – an increasing source of radiation exposure;Brenner;N. Engl. J. Med.,2007
5. Regression forests for efficient anatomy detection and localization in computed tomography scans;Criminisi;Med. Image Anal.,2013