Personne
Laura Ioana Gui
Cette personne n’est plus à l’EPFL
Publications associées (15)
Amygdala volumes and associations with socio-emotional competencies in preterm youth: cross-sectional and longitudinal data
Elda Fischi Gomez, Laura Ioana Gui, Vanessa Siffredi, Petra Susan Hüppi
Background Socio-emotional difficulties often result from very preterm (VPT) birth. The amygdala's developmental trajectory, including its nuclei, has been recognized as a significant factor in observed difficulties. This study aims to assess the relations ...
Springernature2024Behavioral outcome of very preterm children at 5 years of age: Prognostic utility of brain tissue volumes at term-equivalent-age, perinatal, and environmental factors
Djalel Eddine Meskaldji, Laura Ioana Gui, Serafeim Loukas
ObjectivePrematurity is associated with a high risk of long-term behavioral problems. This study aimed to assess the prognostic utility of volumetric brain data at term-equivalent-age (TEA), clinical perinatal factors, and parental social economic risk in ...
WILEY2023Music enhances structural maturation of emotional processing neural pathways in very preterm infants
Nicolas Kunz, Laura Ioana Gui, François Lazeyras
Prematurity disrupts brain maturation by exposing the developing brain to different noxious stimuli present in the neonatal intensive care unit (NICU) and depriving it from meaningful sensory inputs during a critical period of brain development, leading to ...
2020Longitudinal study of neonatal brain tissue volumes in preterm infants and their ability to predict neurodevelopmental outcome
Djalel Eddine Meskaldji, Laura Ioana Gui, Serafeim Loukas
Premature birth has been associated with poor neurodevelopmental outcomes. However, the relation between such outcomes and brain growth in the neonatal period has not yet been fully elucidated. This study investigates longitudinal brain development between ...
ACADEMIC PRESS INC ELSEVIER SCIENCE2019Evaluation of automatic neonatal brain segmentation algorithms: The NeoBrainS12 challenge
Elda Fischi Gomez, Laura Ioana Gui
A number of algorithms for brain segmentation in preterm born infants have been published, but a reliable comparison of their performance is lacking. The NeoBrainS12 study (http://neobrains12.isi.uu.nl), providing three different image sets of preterm born ...
Elsevier Science Bv2015Regional changes of cortical thickness and cortical surface in children born prematurely and children born with intrauterine growth restriction at school age
Elda Fischi Gomez, Laura Ioana Gui, François Lazeyras
Premature birth and the early exposure to environmental sensory information influence the cascade of histogenetic events that occur during the development of human telencephalon. The prenatal establishment of the genetically driven number and size of the e ...
2013Morphology-driven automatic segmentation of MR images of the neonatal brain
Michel Kocher, Laura Ioana Gui, François Lazeyras, Radoslaw Lisowski
The segmentation of MR images of the neonatal brain is an essential step in the study and evaluation of infant brain development. State-of-the-art methods for adult brain MRI segmentation are not applicable to the neonatal brain, due to large differences i ...
Elsevier Science Bv2012Cooperative Object Segmentation and Behavior Inference in Image Sequences
Jean-Philippe Thiran, Laura Ioana Gui
In this paper, we propose a general framework for fusing bottom-up segmentation with top-down object behavior inference over an image sequence. This approach is beneficial for both tasks, since it enables them to cooperate so that knowledge relevant to eac ...
2009A Probabilistic Temporal Model for Joint Attribute Extraction and Behavior Recognition
Jean-Philippe Thiran, Laura Ioana Gui
The focus of this paper is on the recognition of single object behavior from monocular image sequences. The general literature trend is to perform behavior recognition separately after an initial phase of feature/attribute extraction. We propose a framewor ...
2009A collaborative approach to image segmentation and behavior recognition from image sequences
Visual behavior recognition is currently a highly active research area. This is due both to the scientific challenge posed by the complexity of the task, and to the growing interest in its applications, such as automated visual surveillance, human-computer ...
EPFL2008