Phone: +31 88 75 50565
Nadieh Khalili received her Bachelor of Science degree in Biomedical Engineering at Science & Research University, Tehran, Iran. In 2015 she obtained her MSc magna cum laude in Biomedical Engineering at Bern University, Switzerland. Her Master thesis entitled ”Multi-modal registration of 2D histology images on 3D CT dataset”.
In 2016, Nadieh joined to Image Science Institute as a Ph.D. candidate under the supervision of Dr. Ivana Isgum. Her Ph.D focuses on developing novel deep learning methods for quantitative analysis of neonate and fetal brain MRI.
Papers in international journals
|1.||Assessment of brain injury and brain volumes after posthemorrhagic ventricular dilatation: a nested substudy of the randomized controlled ELVIS trial. Journal of Pediatrics, 2019.|
|2.||Brain and cerebrospinal fluid volumes in fetuses and neonates with antenatal diagnosis of critical congenital heart disease: a longitudinal MRI study. American Journal of Neuroradiology, 2019.|
Papers in conference proceedings
|1.||Convolutional Neural Network-based regression for quantification of brain characteristics using MRI. In: WorldCist: 7th World Conference on Information Systems and Technologies , 2019, pp. 577-586.|
|2.||Automatic segmentation of the intracranial volume in fetal MR images. In: MICCAI Workshop on Fetal and InFant Image analysis (FIFI 2017), 2017.|
|1.||Brain tissue segmentation in fetal MRI using convolutional neural networks with simulated intensity inhomogeneities . International Society for Magnetic Resonance in Medicine, 27th Annual Meeting & Exhibition, 2019.|
|2.||Timing of intervention for posthemorrhagic ventricular dilatation: effect on brain injury and brain volumes on term-equivalent age MRI. Pediatric Academic Societies (PAS) Meeting 2018, 2019.|