Zobrazeno 1 - 10
of 1 175
pro vyhledávání: '"Alexander, Daniel C"'
Autor:
Cicimen, Alp G., Tregidgo, Henry F. J., Figini, Matteo, Messaritaki, Eirini, McNabb, Carolyn B., Palombo, Marco, Evans, C. John, Cercignani, Mara, Jones, Derek K., Alexander, Daniel C.
Prior work on the Image Quality Transfer on Diffusion MRI (dMRI) has shown significant improvement over traditional interpolation methods. However, the difficulty in obtaining ultra-high resolution Diffusion MRI scans poses a problem in training neur
Externí odkaz:
http://arxiv.org/abs/2408.03216
In this work, we introduce Brain Latent Progression (BrLP), a novel spatiotemporal disease progression model based on latent diffusion. BrLP is designed to predict the evolution of diseases at the individual level on 3D brain MRIs. Existing deep gene
Externí odkaz:
http://arxiv.org/abs/2405.03328
Autor:
Kim, Seunghoi, Jin, Chen, Diethe, Tom, Figini, Matteo, Tregidgo, Henry F. J., Mullokandov, Asher, Teare, Philip, Alexander, Daniel C.
Recent developments in diffusion models have advanced conditioned image generation, yet they struggle with reconstructing out-of-distribution (OOD) images, such as unseen tumors in medical images, causing "image hallucination" and risking misdiagnosi
Externí odkaz:
http://arxiv.org/abs/2404.05980
Recent learning-based approaches have made astonishing advances in calibrated medical imaging like computerized tomography (CT), yet they struggle to generalize in uncalibrated modalities -- notably magnetic resonance (MR) imaging, where performance
Externí odkaz:
http://arxiv.org/abs/2311.16914
Low-field (LF) MRI scanners (<1T) are still prevalent in settings with limited resources or unreliable power supply. However, they often yield images with lower spatial resolution and contrast than high-field (HF) scanners. This quality disparity can
Externí odkaz:
http://arxiv.org/abs/2311.06631
Autor:
Shahin, Ahmed H., Zhao, An, Whitehead, Alexander C., Alexander, Daniel C., Jacob, Joseph, Barber, David
Survival analysis is a valuable tool for estimating the time until specific events, such as death or cancer recurrence, based on baseline observations. This is particularly useful in healthcare to prognostically predict clinically important events ba
Externí odkaz:
http://arxiv.org/abs/2309.03851
Autor:
Breen-Norris, James O, Siow, Bernard, Hipwell, Ben, Roberts, Thomas, Lythgoe, Mark F., Ianus, Andrada, Alexander, Daniel C., Walker-Samuel, Simon
The permeability of cell membranes varies significantly across both healthy and diseased tissue, and changes in cell membrane permeability can occur during treatment response in tumours. Measurements of cell membrane permeability could therefore be u
Externí odkaz:
https://ul.qucosa.de/id/qucosa%3A37832
https://ul.qucosa.de/api/qucosa%3A37832/attachment/ATT-0/
https://ul.qucosa.de/api/qucosa%3A37832/attachment/ATT-0/
Autor:
He, Tiantian, Thompson, Elinor, Schroder, Anna, Oxtoby, Neil P., Abdulaal, Ahmed, Barkhof, Frederik, Alexander, Daniel C.
Computational models of neurodegeneration aim to emulate the evolving pattern of pathology in the brain during neurodegenerative disease, such as Alzheimer's disease. Previous studies have made specific choices on the mechanisms of pathology producti
Externí odkaz:
http://arxiv.org/abs/2308.05536
Autor:
Cheung, Wing Keung, Pakzad, Ashkan, Mogulkoc, Nesrin, Needleman, Sarah, Rangelov, Bojidar, Gudmundsson, Eyjolfur, Zhao, An, Abbas, Mariam, McLaverty, Davina, Asimakopoulos, Dimitrios, Chapman, Robert, Savas, Recep, Janes, Sam M, Hu, Yipeng, Alexander, Daniel C., Hurst, John R, Jacob, Joseph
The morphology and distribution of airway tree abnormalities enables diagnosis and disease characterisation across a variety of chronic respiratory conditions. In this regard, airway segmentation plays a critical role in the production of the outline
Externí odkaz:
http://arxiv.org/abs/2308.00008
Autor:
Cheung, Wing Keung, Kalindjian, Jeremy, Bell, Robert, Nair, Arjun, Menezes, Leon J., Patel, Riyaz, Wan, Simon, Chou, Kacy, Chen, Jiahang, Torii, Ryo, Davies, Rhodri H., Moon, James C., Alexander, Daniel C., Jacob, Joseph
Early detection and diagnosis of coronary artery disease (CAD) could save lives and reduce healthcare costs. In this study, we propose a 3D Resnet-50 deep learning model to directly classify normal subjects and CAD patients on computed tomography cor
Externí odkaz:
http://arxiv.org/abs/2308.00009