Feto/neonatal Imaging

Imaging the fetal head to improve long term neurological development. The basis for life-long neuro-cognitive competency is laid during the feto/neonatal period of development. Various factors have an impact on the growing brain and subsequently determine long term development. Diseases originating in this critical period are associated with severe burden to the individual but also to the society, and represent an unmet medical need. Currently, there is a lack in advanced analytical tools for detailed health status assessment in that vulnerable population that would allow personalized medicine to prevent long-term burden. By focusing on the feto/neonatal period of development, it is the objective of our research (i) to improve traditional health assessment tools through artificial intelligent (AI) systems to continuously and accurately monitor neurodevelopment, (ii) to develop advanced analytical tools to monitor clinical factors impacting neurodevelopment and head growth, (iii) to develop personalized strategies for preventing impaired head growth in the feto/neonatal period, and finally (iv) develop personalized and smart therapeutic strategies for treating common head pathologies, namely cranial deformities. Therefore, the my-nEUro-growth initiative was established.

Group leader

Anne Fritze

Collaborations

Helena Torres; Institutio Politecnico do Cavado e do Ave (IPCA), Portugal;

Marijn Vermeulen; Erasmus University Rotterdam (ERASMUS MC), Netherlands;

Fundacion BMaterials (BCM), Spain;

Warzawski Uniwersitytet Medyzny (WUM), Poland;

Khaled Ismail: Department of Gynecology and Obstetrics; Faculty of Medicine in Pilsen, Charles University; Biomedical Center; Faculty of Medicine in Pilsen;

Hans-Gerd Maas; TU Dresden, Institute for Photogrammetry (TUD-IP);

Sandra Hunger; Werkzeugmaschinen und Umformtechnik IWU, Abteilung Medizintechnik, Fraunhofer Institut (FHI)

Doctoral Students

Selected Publications

Obstetric forceps dimensions and the newborn head biometry: Time for an update. Ismail AT, Fritze A, Rüdiger M, Ismail KM.Eur J Obstet Gynecol Reprod Biol. 2020 Nov 26;256:270-273. doi: 10.1016/j.ejogrb.2020.11.046. Online ahead of print.

Anthropometric Landmark Detection in 3D Head Surfaces using a Deep Learning Approach. Torres HR; Morais P; Fritze A; Oliveira B; Veloso F; Rüdiger M; Fonseca JC; Vilaca JL; IEEE J Biomed Health Inform. 2020 Nov 4;PP. doi: 10.1109/JBHI.2020.3035888. Online ahead of print.PMID: 33147152

Non-invasive estimation of brain-volume in infants. Burkhardt W, Schneider D, Hahn G, Konstantelos D, Maas HG, Rüdiger M. Early Hum Dev. 2019 May;132:52-57. doi: 10.1016/j.earlhumdev.2019.03.020. Epub 2019 Apr 12

Three-dimensional digital imaging to assess newborn biparietal diameter at term. Ismail AT, Rüdiger M, Ismail KMK, Burkhardt W. Eur J Obstet Gynecol Reprod Biol. 2018 Apr;223:143-144. doi: 10.1016/j.ejogrb.2018.02.009

Prevalence of head deformities in preterm infants at term equivalent age. Ifflaender S, Rüdiger M, Konstantelos D, Wahls K, Burkhardt W. Early Hum Dev. 2013 Dec;89(12):1041-7. doi: 10.1016/j.earlhumdev.2013.08.011

Three-dimensional digital capture of head size in neonates - a method evaluation. Ifflaender S, Rüdiger M, Koch A, Burkhardt W. PLoS One. 2013 Apr 8;8(4):e61274. doi: 10.1371/journal.pone.0061274. Print 2013