LABORATORIJ ZA SLIKOVNE TEHNOLOGIJE
Objave - med letoma 1992 in 2017 za člana 'Alfiia Galimzianova' 
 

 
2017
1. Žiga Lesjak, Alfiia Galimzianova, Aleš Koren, Matej Lukin, Franjo Pernuš, Boštjan Likar in Žiga Špiclin. A novel public MR image dataset of multiple sclerosis patients with lesion segmentations based on multi-rater consensus. Neuroinformatics, 2017. [doi:10.1007/s12021-017-9348-7] [FV: 3.200 (2016); 17/105 computer science, interdisciplinary applications; 1. četrtina]
 
2016
2. Alfiia Galimzianova, Franjo Pernuš, Boštjan Likar in 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] [FV: 5.835 (2016); 1/14 neuroimaging; 1. četrtina]
 
2015
3. Alfiia Galimzianova, Franjo Pernuš, Boštjan Likar in 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] [FV: 6.077 (2015); 5/255 engineering, electrical & electronic; 1. četrtina]
 
2016
4. Tim Jerman, Alfiia Galimzianova, Franjo Pernuš, Boštjan Likar in Žiga Špiclin. Combining unsupervised and supervised methods for lesion segmentation. Proceedings of the 1st BrainLes International Workshop held at the 18th International Conference on Medical Image Computing and Computer Assisted Intervention - MICCAI 2015, Lecture Notes in Computer Science 9556:45-56, 2016. [doi:10.1007/978-3-319-30858-6_5]
 
2015
5. Tim Jerman, Alfiia Galimzianova, Franjo Pernuš, Boštjan Likar in Žiga Špiclin. Combining unsupervised and supervised methods for lesion segmentation. Proceedings of the MICCAI Brain Lesions (Brainles) Workshop, 5 Oct, Munich, Germany, 2015.
6. Alfiia Galimzianova, Žiga Lesjak, Boštjan Likar, Franjo Pernuš in Žiga Špiclin. Locally-adaptive MR intensity models and MRF-based segmentation of multiple sclerosis lesions . SPIE Medical Imaging 2015, Image Processing, 21-26 Feb, Orlando FL, USA, S. Ourselin, M.A. Styner (Eds.), 9413:94133G-1-9, 2015. [doi:10.1117/12.2081642]
 
2014
7. Alfiia Galimzianova, Žiga Špiclin, Boštjan Likar in Franjo Pernuš. Robust mixture-parameter estimation for unsupervised segmentation of brain MR images. 3rd International MICCAI Workshop on Medical Computer Vision: Large Data in Medical Imaging - MCV 2013, Sep 26, Nagoya, Japan, B. Menze et al. (Eds.), Lecture Notes in Computer Science 8331:84-94, 2014. [doi:10.1007/978-3-319-05530-5_9]
 
2013
8. Alfiia Galimzianova, Žiga Špiclin, Boštjan Likar in Franjo Pernuš. Automated segmentation of MS lesions in brain MR images using localized trimmed-likelihood estimation. SPIE Medical Imaging 2013, Image Processing, 9-14 Feb, Lake Buena Vista FL, USA, S. Ourselin, D.R. Haynor (Eds.), 8669:86693E, 2013. [doi:10.1117/12.2006381]
 
2015
9. Žiga Lesjak, Alfiia Galimzianova, Boštjan Likar, Franjo Pernuš in Žiga Špiclin. Increased accuracy and reproducibility of MS lesion volume quantification by using publicly available BrainSeg3D image analysis software. Multiple Sclerosis Journal, 21(Suppl. 11):500-501, 2015. [doi:10.1177/1352458515602642] [FV: 4.671 (2015); 27/192 clinical neurology; 1. četrtina]
 

 
Vir: http://lit.fe.uni-lj.si   |   Datum: 22.11.2017   |   Ura: 8:19