Search Results - "Ferrante, Enzo"

Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer’s disease by Parisot, Sarah, Ktena, Sofia Ira, Ferrante, Enzo, Lee, Matthew, Guerrero, Ricardo, Glocker, Ben, Rueckert, Daniel

“…•First application of graph convolutional networks for brain analysis in populations.•Graph based population model that leverages imaging and non-imaging…”
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Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation by Oktay, Ozan, Ferrante, Enzo, Kamnitsas, Konstantinos, Heinrich, Mattias, Wenjia Bai, Caballero, Jose, Cook, Stuart A., de Marvao, Antonio, Dawes, Timothy, O'Regan, Declan P., Kainz, Bernhard, Glocker, Ben, Rueckert, Daniel

“…Incorporation of prior knowledge about organ shape and location is key to improve performance of image analysis approaches. In particular, priors can be useful…”
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Addressing fairness in artificial intelligence for medical imaging by Ricci Lara, María Agustina, Echeveste, Rodrigo, Ferrante, Enzo

“…A plethora of work has shown that AI systems can systematically and unfairly be biased against certain populations in multiple scenarios. The field of medical…”
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Sub-cortical brain structure segmentation using F-CNN'S by Shakeri, Mahsa, Tsogkas, Stavros, Ferrante, Enzo, Lippe, Sarah, Kadoury, Samuel, Paragios, Nikos, Kokkinos, Iasonas

“…In this paper we propose a deep learning approach for segmenting sub-cortical structures of the human brain in Magnetic Resonance (MR) image data. We draw…”
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CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images by Gaggion, Nicolás, Mosquera, Candelaria, Mansilla, Lucas, Saidman, Julia Mariel, Aineseder, Martina, Milone, Diego H., Ferrante, Enzo

“…The development of successful artificial intelligence models for chest X-ray analysis relies on large, diverse datasets with high-quality annotations. While…”
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Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference by Echeveste, Rodrigo, Ferrante, Enzo, Milone, Diego H, Samengo, Inés

“…Theories for autism spectrum disorder (ASD) have been formulated at different levels, ranging from physiological observations to perceptual and behavioral…”
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Slice-to-volume medical image registration: A survey by Ferrante, Enzo, Paragios, Nikos

“…•The first comprehensive survey of the literature about slice-to-volume registration.•A categorical study of the algorithms according to an ad-hoc defined…”
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Metric learning with spectral graph convolutions on brain connectivity networks by Ktena, Sofia Ira, Parisot, Sarah, Ferrante, Enzo, Rajchl, Martin, Lee, Matthew, Glocker, Ben, Rueckert, Daniel

“…Graph representations are often used to model structured data at an individual or population level and have numerous applications in pattern recognition…”
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Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis by Larrazabal, Agostina J., Nieto, Nicolás, Peterson, Victoria, Milone, Diego H., Ferrante, Enzo

“…Artificial intelligence (AI) systems for computer-aided diagnosis and image-based screening are being adopted worldwide by medical institutions. In such a…”
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Learning deformable registration of medical images with anatomical constraints by Mansilla, Lucas, Milone, Diego H., Ferrante, Enzo

“…Deformable image registration is a fundamental problem in the field of medical image analysis. During the last years, we have witnessed the advent of deep…”
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Graph-Based Slice-to-Volume Deformable Registration by Ferrante, Enzo, Paragios, Nikos

“…Deformable image registration is a fundamental problem in computer vision and medical image computing. In this paper we investigate the use of graphical models…”
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Post-DAE: Anatomically Plausible Segmentation via Post-Processing With Denoising Autoencoders by Larrazabal, Agostina J., Martinez, Cesar, Glocker, Ben, Ferrante, Enzo

“…We introduce Post-DAE, a post-processing method based on denoising autoencoders (DAE) to improve the anatomical plausibility of arbitrary biomedical image…”
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Improving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis by Gaggion, Nicolas, Mansilla, Lucas, Mosquera, Candelaria, Milone, Diego H., Ferrante, Enzo

“…Anatomical segmentation is a fundamental task in medical image computing, generally tackled with fully convolutional neural networks which produce dense…”
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Class imbalance on medical image classification: towards better evaluation practices for discrimination and calibration performance by Mosquera, Candelaria, Ferrer, Luciana, Milone, Diego H., Luna, Daniel, Ferrante, Enzo

“…Purpose This work aims to assess standard evaluation practices used by the research community for evaluating medical imaging classifiers, with a specific focus…”
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Weakly Supervised Learning of Metric Aggregations for Deformable Image Registration by Ferrante, Enzo, Dokania, Puneet Kumar, Silva, Rafael Marini, Paragios, Nikos

“…Deformable registration has been one of the pillars of biomedical image computing. Conventional approaches refer to the definition of a similarity criterion…”
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Deep net detection and onset prediction of electrographic seizure patterns in responsive neurostimulation by Peterson, Victoria, Kokkinos, Vasileios, Ferrante, Enzo, Walton, Ashley, Merk, Timon, Hadanny, Amir, Saravanan, Varun, Sisterson, Nathaniel, Zaher, Naoir, Urban, Alexandra, Richardson, R. Mark

“…Objective Managing the progress of drug‐resistant epilepsy patients implanted with the Responsive Neurostimulation (RNS) System requires the manual evaluation…”
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Supervision by Denoising by Young, Sean I., Dalca, Adrian V., Ferrante, Enzo, Golland, Polina, Metzler, Christopher A., Fischl, Bruce, Iglesias, Juan Eugenio

“…Learning-based image reconstruction models, such as those based on the U-Net, require a large set of labeled images if good generalization is to be guaranteed…”
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Fitting Skeletal Models via Graph-Based Learning by Gaggion, Nicolas, Ferrante, Enzo, Paniagua, Beatriz, Vicory, Jared

“…Skeletonization is a popular shape analysis technique that models an object's interior as opposed to just its boundary. Fitting template-based skeletal models…”
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Domain Generalization via Gradient Surgery by Mansilla, Lucas, Echeveste, Rodrigo, Milone, Diego H., Ferrante, Enzo

“…In real-life applications, machine learning models often face scenarios where there is a change in data distribution between training and test domains. When…”
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Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study by Monteiro, Miguel, Newcombe, Virginia F J, Mathieu, Francois, Adatia, Krishma, Kamnitsas, Konstantinos, Ferrante, Enzo, Das, Tilak, Whitehouse, Daniel, Rueckert, Daniel, Menon, David K, Glocker, Ben

“…CT is the most common imaging modality in traumatic brain injury (TBI). However, its conventional use requires expert clinical interpretation and does not…”
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