Mostrando 7 resultados de: 7
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2022 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2022 - Proceedings(2)
Progress in Biomedical Optics and Imaging - Proceedings of SPIE(2)
Medical Image Analysis(1)
Neural Networks(1)
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Medicina y salud(6)
Ciencias de la computación(3)
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Ginecología, obstetricia, pediatría, geriatría(1)
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:googlescopusMeasuring the Impact of Data Augmentation Techniques in Lung Radiograph Classification Using a Fractional Factorial Design: A Covid-19 Case Study
Conference ObjectAbstract: Convolutional neural networks (CNNs) have become dominant in various computer vision tasks, obtaininPalabras claves:convolutional neural networks, Covid-19 Detection, design of experiments, Fractional Factorial Design, Image Data Augmentation, Medical Image ClassificationAutores:Bernardo Puente-Mejia, Daniel Riofrio, Danny Navarrete, Diego S. Benitez, Jose Murillo J., Maria G. Baldeon Calisto, Mateo Hidalgo Davila, Noel Perez, Ricardo Flores MoyanoFuentes:scopusU-Net Variations for Spontaneous Intracranial Hemorrhages Detection on CT Images
Conference ObjectAbstract: Brain injuries represent one of the most severe medical problems that affect people health worldwidePalabras claves:Computerized tomography scan, Convolutional neural network, deep learning, ICH, image segmentation, U-netAutores:Daniel Riofrio, Diego S. Benitez, Luis A. Erazo, Maria G. Baldeon Calisto, Noel Perez, Ricardo Flores MoyanoFuentes: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:googlescopusStac-Da: Structure Aware Cross-Modality Domain Adaptation Framework with Image and Feature Level Adaptation for Medical Image Segmentation
OtherAbstract: In this work, we present an unsupervised Structure Aware Cross-modality Domain Adaptation (StAC-DA)Palabras claves:Autores:Maria G. Baldeon CalistoFuentes:google