[Unknown], ENIGMA, Petrov, D, Gutman, BA, Yu, S-HJ, van Erp, TGM, Schmaal, L, Veltman, D, Alpert, K, Isaev, D, Zavaliangos-Petropulu, A, Ching, CRK, Calhoun, V, Glahn, D, Satterthwaite, TD, Andreasen, OA, Borgwardt, S, Howells, F, Groenewold, N, Voineskos, A, Radua, J, Potkin, SG, Crespo-Facorro, B, Tordesillas-Gutiérrez, D, Shen, L, Lebedeva, I, Spalletta, G, Donohoe, G, Kochunov, P, Rosa, PGP, James, A, Dannlowski, U, Baune, BT, Aleman, A, Gotlib, IH, Walter, H, Walter, M, Soares, JC, Ehrlich, S, Gur, RC, Doan, NT, Agartz, I, Westlye, LT, Harrisberger, F, Riecher-Rössler, A, Uhlmann, A, Stein, DJ, Dickie, EW, Pomarol-Clotet, E, Fuentes-Claramonte, P, Canales-Rodríguez, EJ
& Walton, E 2017,
Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging. in Q Wang, Y Shi, HI Suk & K Suzuki (eds),
Machine Learning in Medical Imaging. MLMI 2017. Lecture Notes in Computer Science, vol. 10541, Springer, Cham, Switzerland, pp. 371-378, 8th International Workshop on Machine Learning in Medical Imaging (MLMI), 2017, Quebec City, Canada,
10/09/17.
https://doi.org/10.1007/978-3-319-67389-9_43