Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Francis Dutil"'
Autor:
Marion Tonneau, Kim Phan, Venkata S. K. Manem, Cecile Low-Kam, Francis Dutil, Suzanne Kazandjian, Davy Vanderweyen, Justin Panasci, Julie Malo, François Coulombe, Andréanne Gagné, Arielle Elkrief, Wiam Belkaïd, Lisa Di Jorio, Michele Orain, Nicole Bouchard, Thierry Muanza, Frank J. Rybicki, Kam Kafi, David Huntsman, Philippe Joubert, Florent Chandelier, Bertrand Routy
Publikováno v:
Frontiers in Oncology, Vol 13 (2023)
BackgroundRecent developments in artificial intelligence suggest that radiomics may represent a promising non-invasive biomarker to predict response to immune checkpoint inhibitors (ICIs). Nevertheless, validation of radiomics algorithms in independe
Externí odkaz:
https://doaj.org/article/1c9b27366e80483d88227a18e19ca975
Autor:
Marion Tonneau, Kim Phan, Cécile Low-Kam, Francis Dutil, Suzanne Kazandjian, Davy Vanderweyen, Justin Panasci, Julie Malo, François Coulombe, Arielle Elkrief, Wiam Belkaïd, Lisa Di Jorio, Michèle Orain, Nicole Bouchard, Thierry Muanza, Kam Kafi, Florent Chandelier, Philippe Joubert, Bertrand Routy
Publikováno v:
Regular and Young Investigator Award Abstracts.
Autor:
Margaux Luck, Yoshua Bengio, Lisa Di Jorio, Tess Berthier, Francis Dutil, Devon Hjelm, Tristan Sylvain
Publikováno v:
ICASSP
In hospitals, data are siloed to specific information systems that make the same information available under different modalities such as the different medical imaging exams the patient undergoes (CT scans, MRI, PET, Ultrasound, etc.) and their assoc
Autor:
Francis Dutil, Thomas Fevens, Qicheng Lao, Mehrzad Mortazavi, Marzieh S. Tahaei, Mohammad Havaei
In this paper, we propose a general framework in continual learning for generative models: Feature-oriented Continual Learning (FoCL). Unlike previous works that aim to solve the catastrophic forgetting problem by introducing regularization in the pa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d4d0b6ff4768cf94c30a84b584e14ddc
Autor:
Chaolu Feng, Paul Suetens, Oskar Maier, Daniel Rueckert, Linmin Pei, Paul Bentley, Christian Ledig, Janina von der Gablentz, Frederik Maes, Matthias Liebrand, Eero Salli, Chris Pal, Richard McKinley, Heinz Handels, Roland Wiest, Jia-Hong Lee, Stefan Winzeck, Ching-Wei Wang, Karl Egger, Francis Dutil, Liang Chen, Jan S. Kirschke, Matthias Wilms, Janaki Raman Rangarajan, Hanna-Leena Halme, Konstantinos Kamnitsas, Ulrike M. Krämer, Levin Häni, Ben Glocker, Michael Götz, Mattias P. Heinrich, Abdul Basit, Mohammad Havaei, David Robben, Hugo Larochelle, Daan Christiaens, Khan M. Iftekharuddin, Syed M. S. Reza, Antti Korvenoja, Bjoern H. Menze, John Muschelli, Qaiser Mahmood, Tom Haeck, Peter Schramm, Thomas F. Münte, Klaus H. Maier-Hein, Elias Kellner, Pierre-Marc Jodoin, Mauricio Reyes
Publikováno v:
Medical Image Analysis. 35:250-269
Ischemic stroke is the most common cerebrovascular disease, and its diagnosis, treatment, and study relies on non-invasive imaging. Algorithms for stroke lesion segmentation from magnetic resonance imaging (MRI) volumes are intensely researched, but
Autor:
Thomas Fevens, Lisa Di Jorio, Francis Dutil, Mohammad Havaei, Ahmad Pesaranghader, Qicheng Lao
Publikováno v:
ICCV
Synthesizing images from a given text description involves engaging two types of information: the content, which includes information explicitly described in the text (e.g., color, composition, etc.), and the style, which is usually not well describe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11b455cb3e779415da797b574e83ddbb
http://arxiv.org/abs/1908.05324
http://arxiv.org/abs/1908.05324
Autor:
Lisa Di Jorio, Saeid Asgari Taghanaki, Yoshua Bengio, Ghassan Hamarneh, Mohammad Havaei, Tess Berthier, Francis Dutil
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030322250
MICCAI (6)
MICCAI (6)
The scarcity of richly annotated medical images is limiting supervised deep learning based solutions to medical image analysis tasks, such as localizing discriminatory radiomic disease signatures. Therefore, it is desirable to leverage unsupervised a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::597b2efd6df90c85bb8a427813be506e
https://doi.org/10.1007/978-3-030-32226-7_82
https://doi.org/10.1007/978-3-030-32226-7_82
Publikováno v:
Rep4NLP@ACL
Generative Adversarial Networks (GANs) have gathered a lot of attention from the computer vision community, yielding impressive results for image generation. Advances in the adversarial generation of natural language from noise however are not commen
Publikováno v:
Rep4NLP@ACL
We investigate the integration of a planning mechanism into an encoder-decoder architecture with attention. We develop a model that can plan ahead when it computes alignments between the source and target sequences not only for a single time-step but
Publikováno v:
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries ISBN: 9783319308579
Brainles@MICCAI
Brainles@MICCAI
We consider the problem of fully automatic brain focal pathology segmentation, in MR images containing low and high grade gliomas and ischemic stroke lesion. We propose a Convolutional Neural Network (CNN) approach which is amongst the top performing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c3728b9e1740b437a11126a609b934bb
https://doi.org/10.1007/978-3-319-30858-6_17
https://doi.org/10.1007/978-3-319-30858-6_17