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

Diploma iz fizike (Univerza v Ljubljani, Fakulteta za matematiko in fiziko)

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

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

Tim Jerman, Aichi Chien, Franjo Pernuš, Boštjan Likar, Žiga Špiclin: Automated cutting plane positioning for intracranial aneurysm quantification. IEEE Transactions on Biomedical Engineering, 67(2):577-587, 2020 [doi:10.1109/TBME.2019.2918921 ] [COBISS-ID:12543316 ]

Tim Jerman, Franjo Pernuš, Boštjan Likar, Žiga Špiclin: Blob enhancement and visualization for improved intracranial aneurysm detection. IEEE Transactions on Visualization and Computer Graphics, 22(6):1705-1717, 2016 [doi:10.1109/TVCG.2015.2446493 ] [COBISS-ID:11077716 ]

Tim Jerman, Franjo Pernuš, Boštjan Likar, Žiga Špiclin: Enhancement of vascular structures in 3D and 2D angiographic images. IEEE Transactions on Medical Imaging, 35(9):2107-2118, 2016 [doi:10.1109/TMI.2016.2550102 ] [COBISS-ID:11325268 ]

Žiga Bizjak, Tim Jerman, Boštjan Likar, Franjo Pernuš, Aichi Chien, Žiga Špiclin: Registration based detection and quantification of intracranial aneurysm growth. SPIE Medical Imaging 2019: Computer-Aided Diagnosis, Feb 16-21, San Diego, CA, USA (K. Mori, H. K. Hahn, Eds.), 10950:1095007, 2019 [doi:10.1117/12.2512781 ] [COBISS-ID:12500564 ]

Domen Ravnik, Tim Jerman, Franjo Pernuš, Boštjan Likar, Žiga Špiclin: Dataset variability leverages white-matter lesion segmentation performance with convolutional neural network. SPIE Medical Imaging 2018: Image Processing, Feb 10-15, Houston, TX, USA (E. D. Angelini, B. A. Landman, Eds.), 10574:105741J, 2018 [doi:10.1117/12.2293702 ] [COBISS-ID:11988308 ]