SharePoint

Suche Sitemap

Das Forschungszentrum für das Kind FZK

Das Forschungzentrum (FZK) hat sich zum Ziel gesetzt, beste Ergebnisse in den relevanten Bereichen Prävention, Wiederherstellung und Heilung von Krankheiten, Verletzungen und Fehlbildungen zu erreichen, und zwar vom Neugeborenen bis zum Jugendlichen.

Fetal Developmental Imaging

Team

András Jakab, PD Dr. med-univ. PhD
Publications and ZNZ Profile

 

Kelly Payette, M.sc.
Doctoral student, Neuroscience PhD Program

 

Hui Ji, M.D.
Doctoral student, MD-PhD Program


Céline Steger, M.sc.
Doctoral student, Neuroscience PhD Program
Working in the research project "Altered cerebral growth and development in infants with congenital heart disease", lead by Prof. Walter Knirsch

 

Maria Karatsoli, M.sc.

Research Assistant / Doctoral student, Neuroscience PhD Program
Co-working at the Brain Research Institute, University of Zurich

 

Visiting, master's thesis and medical doctoral thesis students / alumni:

Cosima Ruzzo (master's thesis, led by Kelly Payette)
Marcel Burri (master's thesis, collaboration by Kelly Payette, led by Martin Melchior, FHNW)
Nikola Rakic (medical doctoral dissertation)
Lin Zhang (alumni, master's thesis, currently: ETH-CVL)
Roxane Licandro (alumni, visiting research project, Medical University of Vienna)
Tabitha Roth (alumni, semester project, ETH)

Top

Kontakt

PD Dr. Andras Jakab,

andras.jakab@kispi.uzh.ch

Kinderspital Zürich – Eleonorenstiftung
Zentrum für MR-Forschung
Steinwiesstrasse 75
CH-8032 Zürich

Top

Publikationen

SELECTED PUBLICATIONS

 

Feldmann M, Guo T, Miller SP, Knirsch W, Kottke R, Hagmann C, Latal B, Jakab A (2020) Delayed maturation of the structural brain connectome in neonates with congenital heart disease. Brain: Communications (accepted manuscript in press).

 

Jakab A, Natalucci G, Koller B, Tuura R, Ruegger C, Hagmann C (2020) Mental development is associated with cortical connectivity of the ventral and nonspecific thalamus of preterm newborns. Brain and Behavior, 10:e01786.

 

Payette K, Kottke R, Ji H, Jakab A. (2020) Efficient multi-class fetal brain segmentation in high resolution MRI reconstructions with noisy labels. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020, 12437 LNCS, pp. 295-304. Springer, Cham.

 

Payette K, Moehrlen U, Mazzone L, Ochsenbein-Kölble N, Tuura R, Kottke R, Meuli M, Jakab A (2019) Longitudinal Analysis of Fetal MRI in Patients with Prenatal Spina Bifida Repair. In: Wang Q. et al. (eds) Smart Ultrasound Imaging and Perinatal, Preterm and Paediatric Image Analysis. PIPPI 2019, SUSI 2019. Lecture Notes in Computer Science, vol 11798. Springer, Cham.

 

Jakab A, Meuwly E, Feldmann M, von Rhein M, Kottke R, Tuura R, Latal B, Knirsch W. (2019) Left temporal plane growth predicts language development in newborns with congenital heart disease. Brain, 142: 1270–1281.

 

Meuwly E, Feldmann M, Knirsch W, von Rhein M, Payette K, Dave H, Tuura R, Kottke R, Hagmann C, Latal B, Jakab A (2019) Postoperative brain volumes are associated with one-year neurodevelopmental outcome in children with severe congenital heart disease. Scientific Reports 9: 10885

 

Jakab A, Tuura R, Kellenberger C, Scheer I. (2017) In utero diffusion tensor imaging of the fetal brain: a reproducibility study.  NeuroImage: Clinical 15: 601-612.

Top

 

We are an interdisciplinary research group and part of the Center for MR-Research, University Children's Hospital Zürich. Our team uses advanced imaging techniques to depict white matter structure, brain connectivity and microvascular brain perfusion, and we aim to study the links between brain structure and function and neurological outcome in common congenital malformations. Our research projects bridge the gap between computational imaging research in 3D microscopic, molecular and MRI techniques and application into clinical care, and thus establish foundations for imaging-driven precision medicine.

 

Fetal Tissue Annotations Dataset and Challenge (FetA): a dataset and public challenge for machine-learning and deep-learning based image segmentation algorithm development 

 

 fetal tissue.png

 

The FetA dataset is a valuable resource for developing automated image segmentation algorithms as it provides open source MRI data and expert manual annotations. The FetA dataset consists of 50 manually annotated, T2-weighted, super-resolution reconstructed in utero fetal MR images. The FetA is a collaborative effort between the following institutions: Center for MR-Research, University Children's Hospital Zürich, Brain Research Institute, University of Zürich, MIALS Lab, CHUV/University of Lausanne, Technical University of München and the University of Debrecen, Hungary. If you would like to have your algorithm tested on the (non-public) testing datasets, please contact us at andras.jakab@kispi.uzh.ch OR kelly.payette@kispi.uzh.ch

The FetA dataset is archived at OpenNeuro, and is available for non-medical research purposes (algorithm development): https://openneuro.org/datasets/ds003105/versions/1.0.1
Please cite our publication pre-print if you are using the dataset: https://arxiv.org/abs/2010.15526

Morphology and connectivity of the developing human brain

Fetal_Developmental_Imaging.png


Fetal magnetic resonance imaging (MRI) is a cutting-edge, noninvasive medical diagnostic procedure that is used to diagnose abnormalities before birth. Our research allows the visualisation of the 3D structure of the developing fiber connectivity of the fetal brain. We are interested in how this novel technology can support clinical decision making and how the in vivo – in utero approach can extend our current knowledge of human brain development. To reveal the microstructural properties and neuronal populations of the developing human brain, we are using novel 3D microscopic imaging techniques, such as the mesoSPIM microscope at the University of Zürich.

Video about this research: https://www.youtube.com/watch?v=xChlqbwFwsE

 

FUNDING

 

Our research is supported by research grants offered to PD Dr. Andras Jakab by the Swiss National Science Foundation (SPARK Grant),  Novartis Foundation for Medical-Biological Research, Forschungszentrum für das Kind (FZK Grant), the OPO-Foundation, Anna-Müller Grocholski Foundation, the Hasler foundation, the EMDO foundation, Neuroscience Center Zürich PhD Grant, Prof. Max Cloetta Foundation and the Foundation for Research in Science and the Humanities at the University of Zurich.

Top
SHPTAPPEXTVM, 192.168.85.281.0.0.0