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Progress in Biomedical Optics and Imaging - Proceedings of SPIE(3)
Artificial Intelligence in Medicine(1)
IISE Annual Conference and Expo 2018(1)
Medical Image Analysis(1)
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google(8)
C-MADA: Unsupervised Cross-Modality Adversarial Domain Adaptation framework for Medical Image Segmentation
Conference ObjectAbstract: Deep learning models have obtained state-of-the-art results for medical image analysis. However, CNNPalabras claves:Domain Adaptation, Generative Adversarial Networks, image segmentation, Medical image analysis, unsupervised learningAutores:Lai-Yuen S.K., Maria G. Baldeon CalistoFuentes:googlescopusCrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation
OtherAbstract: Domain Adaptation (DA) has recently been of strong interest in the medical imaging community. WhilePalabras claves:Domain Adaptation, segmentation, Vestibular schwannomaAutores:Bakas S., Batmanghelich K., Belkov A., Cardoso J., Choi J.W., Dawant B.M., Dong H., Dorent R., Escalera S., Fan Y., Glocker B., Hansen L., Heinrich M.P., Ivory M., Joshi S., Joutard S., Kashtanova V., Kim H.G., Kondo S., Kruse C.N., Kujawa A., Lai-Yuen S.K., Li H., Liu H., Ly B., Maria G. Baldeon Calisto, Modat M., Oguz I., Ourselin S., Rieke N., Shapey J., Shin H., Shirokikh B., Su Z., Vercauteren T., Wang G., Wu J., Xu Y., Yao K., Zhang L.Fuentes:googlescopusAdaEn-Net: An ensemble of adaptive 2D–3D Fully Convolutional Networks for medical image segmentation
ArticleAbstract: Fully Convolutional Networks (FCNs) have emerged as powerful segmentation models but are usually desPalabras claves:deep learning, Hyperparameter optimization, Medical image segmentation, Multiobjective optimization, Neural Architecture SearchAutores:Lai-Yuen S.K., Maria G. Baldeon CalistoFuentes:googlescopusAdaResU-Net: Multiobjective adaptive convolutional neural network for medical image segmentation
ArticleAbstract: Adapting an existing convolutional neural network architecture to a specific dataset for medical imaPalabras claves:convolutional neural networks, deep learning, Evolutionary algorithms, Hyperparameter optimization, Medical image segmentation, Multiobjective optimizationAutores:Lai-Yuen S.K., Maria G. Baldeon CalistoFuentes:googlescopusEMONAS-Net: Efficient multiobjective neural architecture search using surrogate-assisted evolutionary algorithm for 3D medical image segmentation
ArticleAbstract: Deep learning plays a critical role in medical image segmentation. Nevertheless, manually designingPalabras claves:AutoML, convolutional neural networks, Hyperparameter optimization, Medical image segmentation, Multiobjective optimization, Neural Architecture SearchAutores:Lai-Yuen S.K., Maria G. Baldeon CalistoFuentes:googlescopusEMONAS: Efficient multiobjective neural architecture search framework for 3D medical image segmentation
Conference ObjectAbstract: Deep learning plays a critical role in medical image segmentation. Nevertheless, manually designingPalabras claves:deep learning, Hyperparameter optimization, Medical image segmentation, Multiobjective optimization, Neural Architecture SearchAutores:Lai-Yuen S.K., Maria G. Baldeon CalistoFuentes:googlescopusSelf-adaptive 2D-3D ensemble of fully convolutional networks for medical image segmentation
Conference ObjectAbstract: Segmentation is a critical step in medical image analysis. Fully Convolutional Networks (FCNs) havePalabras claves:deep learning, Hyperparameter optimization, Medical image segmentation, Multiobjective optimization, Neural Architecture SearchAutores:Lai-Yuen S.K., Maria G. Baldeon CalistoFuentes:googlescopusResU-Net: Residual convolutional neural network for prostate MRI segmentation
Conference ObjectAbstract: The identification and segmentation of the prostate on magnetic resonance images (MRI) can assist inPalabras claves:convolutional neural networks, deep learning, image segmentation, medical image processingAutores:Lai-Yuen S.K., Maria G. Baldeon CalistoFuentes:googlescopus