Zobrazeno 1 - 10
of 158
pro vyhledávání: '"Deprez, Maria"'
Autor:
Dong, Yilan, Kyriakopoulou, Vanessa, Grigorescu, Irina, McAlonan, Grainne, Batalle, Dafnis, Deprez, Maria
Numerous studies have highlighted that atypical brain development, particularly during infancy and toddlerhood, is linked to an increased likelihood of being diagnosed with a neurodevelopmental condition, such as autism. Accurate brain tissue segment
Externí odkaz:
http://arxiv.org/abs/2408.15198
Autor:
Munroe, Lindsay, da Silva, Mariana, Heidari, Faezeh, Grigorescu, Irina, Dahan, Simon, Robinson, Emma C., Deprez, Maria, So, Po-Wah
Clinical adoption of deep learning models has been hindered, in part, because the black-box nature of neural networks leads to concerns regarding their trustworthiness and reliability. These concerns are particularly relevant in the field of neuroima
Externí odkaz:
http://arxiv.org/abs/2406.17792
Autor:
Ramirez, Paula, Uus, Alena, van Poppel, Milou P. M., Grigorescu, Irina, Steinweg, Johannes K., Lloyd, David F. A., Pushparajah, Kuberan, King, Andrew P., Deprez, Maria
Publikováno v:
Machine.Learning.for.Biomedical.Imaging. 2 (2023)
Congenital Heart Disease (CHD) is a group of cardiac malformations present already during fetal life, representing the prevailing category of birth defects globally. Our aim in this study is to aid 3D fetal vessel topology visualisation in aortic arc
Externí odkaz:
http://arxiv.org/abs/2311.07234
Autor:
Payette, Kelly, Uus, Alena, Verdera, Jordina Aviles, Zampieri, Carla Avena, Hall, Megan, Story, Lisa, Deprez, Maria, Rutherford, Mary A., Hajnal, Joseph V., Ourselin, Sebastien, Tomi-Tricot, Raphael, Hutter, Jana
Fetal Magnetic Resonance Imaging at low field strengths is emerging as an exciting direction in perinatal health. Clinical low field (0.55T) scanners are beneficial for fetal imaging due to their reduced susceptibility-induced artefacts, increased T2
Externí odkaz:
http://arxiv.org/abs/2308.04903
Autor:
Payette, Kelly, Uus, Alena U., Aviles Verdera, Jordina, Hall, Megan, Egloff, Alexia, Deprez, Maria, Tomi-Tricot, Raphaël, Hajnal, Joseph V., Rutherford, Mary A., Story, Lisa, Hutter, Jana
Publikováno v:
In Medical Image Analysis January 2025 99
Autor:
Cordero-Grande, Lucilio, Ortuño-Fisac, Juan Enrique, Uus, Alena, Deprez, Maria, Santos, Andrés, Hajnal, Joseph V., Ledesma-Carbayo, María Jesús
Magnetic resonance imaging of whole fetal body and placenta is limited by different sources of motion affecting the womb. Usual scanning techniques employ single-shot multi-slice sequences where anatomical information in different slices may be subje
Externí odkaz:
http://arxiv.org/abs/2111.00102
Autor:
Avena-Zampieri, Carla L., Hutter, Jana, Uus, Alena, Deprez, Maria, Payette, Kelly, Hall, Megan, Bafadhel, Mona, Russell, Richard E.K., Milan, Anna, Rutherford, Mary, Shennan, Andrew, Greenough, Anne, Story, Lisa
Publikováno v:
In European Journal of Obstetrics & Gynecology and Reproductive Biology February 2024 293:106-114
Autor:
Grigorescu, Irina, Uus, Alena, Christiaens, Daan, Cordero-Grande, Lucilio, Hutter, Jana, Edwards, A. David, Hajnal, Joseph V., Modat, Marc, Deprez, Maria
Tracking microsctructural changes in the developing brain relies on accurate inter-subject image registration. However, most methods rely on either structural or diffusion data to learn the spatial correspondences between two or more images, without
Externí odkaz:
http://arxiv.org/abs/2005.06926
Autor:
Grigorescu, Irina, Cordero-Grande, Lucilio, Edwards, A David, Hajnal, Jo, Modat, Marc, Deprez, Maria
The use of convolutional neural networks (CNNs) for classification tasks has become dominant in various medical imaging applications. At the same time, recent advances in interpretable machine learning techniques have shown great potential in explain
Externí odkaz:
http://arxiv.org/abs/1910.00071