Zobrazeno 1 - 10
of 8 246
pro vyhledávání: '"Hajnal, A."'
Autor:
Verdera, Jordina Aviles, Silva, Sara Neves, Tomi-Tricot, Raphael, Hall, Megan, Story, Lisa, Malik, Shaihan J, Hajnal, Joseph V, Rutherford, Mary A, Hutter, Jana
Purpose: To provide real-time quantitative organ-specific information - specifically placental and brain T2* - to allow optimization of the MR examination to the individual patient. Methods: A FIRE-based real-time setup segmenting placenta and fetal
Externí odkaz:
http://arxiv.org/abs/2409.16878
Autor:
Silva, Sara Neves, Woodgate, Tomas, McElroy, Sarah, Cleri, Michela, Clair, Kamilah St, Verdera, Jordina Aviles, Payette, Kelly, Uus, Alena, Story, Lisa, Lloyd, David, Rutherford, Mary A, Hajnal, Joseph V, Pushparajah, Kuberan, Hutter, Jana
Two subsequent deep learning networks, one localizing the fetal chest and one identifying a set of landmarks on a coronal whole-uterus balanced steady-state free precession scan, were trained on 167 and 71 fetal datasets across field strengths, acqui
Externí odkaz:
http://arxiv.org/abs/2408.06326
Autor:
West, Daniel J, Glang, Felix, Endres, Jonathan, Leitão, David, Zaiss, Moritz, Hajnal, Joseph V, Malik, Shaihan J
MRI systems are traditionally engineered to produce close to idealized performance, enabling a simplified pulse sequence design philosophy. An example of this is control of eddy currents produced by gradient fields; usually these are compensated by p
Externí odkaz:
http://arxiv.org/abs/2403.17575
Autor:
Dannecker, Maik, Kyriakopoulou, Vanessa, Cordero-Grande, Lucilio, Price, Anthony N., Hajnal, Joseph V., Rueckert, Daniel
We introduce a conditional implicit neural atlas (CINA) for spatio-temporal atlas generation from Magnetic Resonance Images (MRI) of the neurotypical and pathological fetal brain, that is fully independent of affine or non-rigid registration. During
Externí odkaz:
http://arxiv.org/abs/2403.08550
Autor:
Silva, Sara Neves, McElroy, Sarah, Verdera, Jordina Aviles, Colford, Kathleen, Clair, Kamilah St, Tomi-Tricot, Raphael, Uus, Alena, Ozenne, Valery, Hall, Megan, Story, Lisa, Pushparajah, Kuberan, Rutherford, Mary A, Hajnal, Joseph V, Hutter, Jana
Purpose: Widening the availability of fetal MRI with fully automatic real-time planning of radiological brain planes on 0.55T MRI. Methods: Deep learning-based detection of key brain landmarks on a whole-uterus EPI scan enables the subsequent fully a
Externí odkaz:
http://arxiv.org/abs/2401.10441
Autor:
Venturini, Lorenzo, Budd, Samuel, Farruggia, Alfonso, Wright, Robert, Matthew, Jacqueline, Day, Thomas G., Kainz, Bernhard, Razavi, Reza, Hajnal, Jo V.
The current approach to fetal anomaly screening is based on biometric measurements derived from individually selected ultrasound images. In this paper, we introduce a paradigm shift that attains human-level performance in biometric measurement by agg
Externí odkaz:
http://arxiv.org/abs/2401.01201
Autor:
Hajnal, Ákos
This paper presents a novel online learning method that aims at finding a separator hyperplane between data points labelled as either positive or negative. Since weights and biases of artificial neurons can directly be related to hyperplanes in high-
Externí odkaz:
http://arxiv.org/abs/2309.06049
Autor:
Prokopenko, Denis, Hammernik, Kerstin, Roberts, Thomas, Lloyd, David F A, Rueckert, Daniel, Hajnal, Joseph V
Dynamic free-breathing fetal cardiac MRI is one of the most challenging modalities, which requires high temporal and spatial resolution to depict rapid changes in a small fetal heart. The ability of deep learning methods to recover undersampled data
Externí odkaz:
http://arxiv.org/abs/2308.07885
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:
Ma, Qiang, Li, Liu, Kyriakopoulou, Vanessa, Hajnal, Joseph, Robinson, Emma C., Kainz, Bernhard, Rueckert, Daniel
Cortical surface reconstruction plays a fundamental role in modeling the rapid brain development during the perinatal period. In this work, we propose Conditional Temporal Attention Network (CoTAN), a fast end-to-end framework for diffeomorphic neona
Externí odkaz:
http://arxiv.org/abs/2307.11870