ד"ר דפנה לינק-סורני

Rabinowich A., Avisdris N. ,Zilberman A., Link-Sourani D., Lazar S., Herzlich J., Specktor Fadida B., Joskowicz L., Malinger G., Ben-Sira L., Hiersch L., Ben Bashat D.: Reduced adipose tissue in growth-restricted fetuses using quantitative analysis of magnetic resonance images. American Journal of Obstetrics &Gynecology 2023

Avisdris N., Link-Sourani D., Ben-Sira L., Joskowicz L., Malinger G., Yagel S., Miller E., Ben Bashat D.: Improved differentiation between hypo/hypertelorism and normal fetuses based on MRI using automatic ocular biometric measurements, ocular ratios, and machine learning multi-parametric classification. European Radiology 2023, volume 33, pages54–63.

Specktor-Fadida B., Yehuda B., Link-Sourani D., Ben-Sira L., Ben-Bashat D.& Joskowicz L.: Contour Dice Loss for Structures with Fuzzy and Complex Boundaries in Fetal MRI. Computer Vision – ECCV 2022 Workshops pp 355–368.

Avisdris N., Rabinowich A., Fridkin D., Zilberman A., Lazar S., Herzlich J., Hananis Z., Link-Sourani D., Ben-Sira L., Hiersch L., Ben Bashat D. & Joskowicz L.: Automatic Fetal Fat Quantification from MRI. Perinatal, Preterm and Paediatric Image Analysis 2022 pp 25–37.

Specktor Fadida B., Link Sourani D., Ben Sira L., Miller E., Ben Bashat D.& Joskowicz L.: Partial Annotations for the Segmentation of Large Structures with Low Annotation Cost. Medical Image Learning with Limited and Noisy Data 2022 pp 13–22.

Link-Sorani D., Avisdris N., Harel S., Ben Sira L., Ganot T., Gordon Z., Many A., Ben Bashat D.: Ex-vivo MRI of the normal human placenta. Journal of Magnetic Resonance Imaging 2022, Volume56, Issue1, Pages 134-144.

Avisdris N., Yehuda B., Ben-Zvi O., Link-Sourani D., Ben-Sira L., Miller E., Zharkov E., Ben Bashat D., Joskowicz L.: Automatic linear measurements of the fetal brain on MRI with deep neural networks. International journal of computer assisted radiology and surgery 2021, 16(9):1481-1492.

Specktor-Fadida B., Link-Sourani D., Ferster-Kveller S., Ben-Sira L., Miller E., Ben-Bashat D., Joskowicz L.: A Bootstrap Self-training Method for Sequence Transfer: State-of-the-Art Placenta Segmentation in fetal MRI. Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis 2021, pp. 189-199.

Link-Sourani D., Many A., Ben-Sira L., Tarrasch R., Bak S., Kidron D., Gordon Z., Yagel S., Harel S., Ben Bashat D.: Placental vascular tree characterization based on ex-vivo MRI with a potential application for placental insufficiency assessment. Placenta 2020, 96:34-43.

Dudovitch G., Link-Sourani D., Ben Sira L., Miller E., Ben Bashat D., Joskowicz L.: Deep Learning Automatic Fetal Structures Segmentation in MRI Scans with Few Annotated Datasets. Medical Image Computing and Computer Assisted Intervention MICCAI 2020: 365-374.

Link-Sourani D., Braginsky MB., Joskowicz L., Ben Sira L., Harel S., Many A., Tarrasch R., Malinger G., Artzi M., Kapoor C., Miller E., Ben Bashat D.: Automatic Measurement of Fetal Brain Development from Magnetic Resonance Imaging: New Reference Data. Fetal Diagn Ther. 2018;43(2):113-122.

Sourani D., Eitan R., Gordon N., Goelman G.: The habenula couples the dopaminergic and the serotonergic systems: application to depression in Parkinson's disease. Eur J Neurosci. 2012 Sep;36(6):2822-9.

Sourani D., Goelman G.: The interaction between the dopaminergic and the serotonergic systems in the 6-OHDA rat model of Parkinson’s disease. Health 2012; 1218-1224.

Sourani D., Eitan R. and Goelman G.: The Etiology of Depression in Parkinson’s Disease. Nature Precedings 2010.