Doktorat iz elektrotehniških znanosti (Univerza v Ljubljani, Fakulteta za elektrotehniko)

Raziskovalka v Laboratoriju za slikovne tehnologije (Univerza v Ljubljani, Fakulteta za elektrotehniko)

Mladi raziskovalka v Laboratoriju za slikovne tehnologije (Univerza v Ljubljani, Fakulteta za elektrotehniko)

Žiga Lesjak, Alfiia Galimzianova, Aleš Koren, Matej Lukin, Franjo Pernuš, Boštjan Likar, Žiga Špiclin: A novel public MR image dataset of multiple sclerosis patients with lesion segmentations based on multi-rater consensus. Neuroinformatics, 16(1):51-63, 2018 [doi:10.1007/s12021-017-9348-7 ] [COBISS-ID:11896404 ]

Alfiia Galimzianova, Žiga Lesjak, Daniel L. Rubin, Boštjan Likar, Franjo Pernuš, Žiga Špiclin: Locally adaptive magnetic resonance intensity models for unsupervised segmentation of multiple sclerosis lesions. Journal of Medical Imaging, 5(1):011007, 2018 [doi:10.1117/1.JMI.5.1.011007 ] [COBISS-ID:11878484 ]

Alfiia Galimzianova, Franjo Pernuš, Boštjan Likar, Žiga Špiclin: Stratified mixture modeling for segmentation of white-matter lesions in brain MR images. NeuroImage, 124(Part A):1031-1043, 2016 [doi:10.1016/j.neuroimage.2015.09.047 ] [COBISS-ID:11198292 ]

Alfiia Galimzianova, Franjo Pernuš, Boštjan Likar, Žiga Špiclin: Robust estimation of unbalanced mixture models on samples with outliers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(11):2273-2285, 2015 [doi:10.1109/TPAMI.2015.2404835 ] [COBISS-ID:10969940 ]

Myra Cheng, Alfiia Galimzianova, Žiga Lesjak, Žiga Špiclin, Christopher B. Lock, Daniel L. Rubin: A multi-scale multiple sclerosis lesion change detection in a multi-sequence MRI. 4th International Workshop on Deep Learning in Medical Image Analysis - DLMIA 2018 & 8th International Workshop on Multimodal Learning for Clinical Decision Support - ML-CDS 2018, held in conjunction with the 21th International Conference on Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, Sep 20, Granada, Spain (D. Stoyanov et al., Eds.), Lecture Notes in Computer Science 11045:353-360, 2018 [doi:10.1007/978-3-030-00889-5_40 ] [COBISS-ID:12235604 ]