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pro vyhledávání: '"Bulpitt, A"'
Generative modelling for shapes is a prerequisite for In-Silico Clinical Trials (ISCTs), which aim to cost-effectively validate medical device interventions using synthetic anatomical shapes, often represented as 3D surface meshes. However, construct
Externí odkaz:
http://arxiv.org/abs/2403.06317
Autor:
Stone, Rebecca S., Chavarrias-Solano, Pedro E., Bulpitt, Andrew J., Hogg, David C., Ali, Sharib
While several previous studies have devised methods for segmentation of polyps, most of these methods are not rigorously assessed on multi-center datasets. Variability due to appearance of polyps from one center to another, difference in endoscopic i
Externí odkaz:
http://arxiv.org/abs/2309.06807
The fairness of a deep neural network is strongly affected by dataset bias and spurious correlations, both of which are usually present in modern feature-rich and complex visual datasets. Due to the difficulty and variability of the task, no single d
Externí odkaz:
http://arxiv.org/abs/2303.16564
We propose a novel method for generating high-resolution videos of talking-heads from speech audio and a single 'identity' image. Our method is based on a convolutional neural network model that incorporates a pre-trained StyleGAN generator. We model
Externí odkaz:
http://arxiv.org/abs/2209.04252
Deep neural networks are highly susceptible to learning biases in visual data. While various methods have been proposed to mitigate such bias, the majority require explicit knowledge of the biases present in the training data in order to mitigate. We
Externí odkaz:
http://arxiv.org/abs/2204.09389
Autor:
Winder, Christopher, Clark, Matthew, Frood, Russell, Smith, Lesley, Bulpitt, Andrew, Cook, Gordon, Scarsbrook, Andrew
Publikováno v:
In European Journal of Radiology December 2024 181
Publikováno v:
In Medical Image Analysis January 2025 99
Differentiable physics modeling combines physics models with gradient-based learning to provide model explicability and data efficiency. It has been used to learn dynamics, solve inverse problems and facilitate design, and is at its inception of impa
Externí odkaz:
http://arxiv.org/abs/2202.00504
Akademický článek
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Autor:
Ahern, David, Amess, Bob, Ramirez, Kristen Aufiero, Berridge, Georgina, Carroll, Thomas M., Chadwick, Joseph A., Chang, Jaeho, Cheng, Jingfei, Dobbie, Sam T., Drozdz, Magdalena, Fischer, Roman, Frangou, Anna, Fuchs, Hannah S., Griffiths, Lucinda, Inoue, Masato, Jacobs, Brittany-Amber, James, Sabrina A., Kaplinsky, Joseph, Karydis, Ioannis, Kessler, Benedikt M., Lord, Simon R., Lou, Hantao, Lu, Xin, Macri, Mary J., McCann, Katy J., McGregor, Naomi, Middleton, Mark R., Norris-Bulpitt, Stewart, Omiyale, Ayo O., Owen, Richard P., Peneva, Iliana, Phetsouphanh, Chansavath, Rei, Margarida, Ricciardi, Toni, Roth, Andrew, Puig, Carlos Ruiz, Ryan, Aileen, Schuster-Böckler, Benjamin, Siejka-Zielińska, Paulina, Song, Chunxiao, Tomkova, Marketa, Van den Eynde, Benoit J., Velikova, Gergana, Venhaus, Ralph R., White, Michael J., Xie, Phil F.
Publikováno v:
In Cancer Cell 10 July 2023 41(7):1222-1241