2019-02-13. Our paper 'Constrained CNN-losses for weakly supervised segmentation' has been accepted for publication at MedIA journal.
2018-10-20. Our latest
paper 'Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning'and its code have been made available at Arxiv and GitHub.
2018-10-20. Our paper 'HyperDense-Net: A hyper-densely connected CNN for multi-modal segmentation' has been accepted for publication at IEEE Transactions on Medical
Imaging.
2018-10-12.Our paper 'Multi-region segmentation of bladder cancer
structures in MRI with progressive dilated convolutional networks' has been accepted for publication at the journal of Medical Physics. Link.
2018-08-01. The
collation study from the ENIGMA challenge comparing methods for cerebellum parcellation on MRI has been accepted at Neuroimage. Link.
2018-06-15. I have been appointed to Assistant Professor at the department of software and IT and the Ecole de Technologie Superieure, in Montreal,
starting from October,1st.
2018-05-27. Our
paper "Constrained-CNN losses for weakly supervised segmentation"has been accepted as oral at the 1st Conference on Medical Imaging with Deep Learning (MIDL) that will be held in Amsterdam.
2018-02-15. I'll be co-chairing a session on Brain Image
Segmentation at the IEEE International Symposium on Biomedical Imaging (ISBI) 2018 in Washington. DC, USA.
2018-02-08. OurHyperDense network has achieved the
first position at the MRBrains'13 Challenge among 47 teams.
2017-11-29. Our paper
"A 3D fully convolutional neural network and a
random walker to segment the esophagus in CT"has been selected as Editor's
Choice for December 2017 at Medical Physics.
2017-10-20.We have released the code
of our SemiDenseNet CNN for the segmentation of infant brain tissue. Link
2017-10-17. We have submitted our latest network, HyperDenseNet, to ISBI. The arXiv version is available here.
2017-09-14. I will be presenting our
work to segment infant brain tissue with an ensemble of CNNs at the iSEG Grand Challenge 2017 in MICCAI'17, Quebec, Canada.
2017-09-12.Our paper "A 3D fully convolutional neural network and a random walker to segment the esophagus
in CT"has been accepted for publication at Medical Physics. Link
2017-08-05. Our team ranked among the top methods (1st and 2nd
in most of the metrics) on the iSEG Grand MICCAI Challenge 2017 with our
work:"Infant brain tissue
segmentation: an ensemble of semi-dense fully CNNs approach.".
2017-05-30.We have received the "Travel
Student MICCAI award" for our paper"Unbiased shape compactness for segmentation".
2017-05-16.Our latest paper "Unbiased shape compactness for segmentation" has been accepted at MICCAI 2017.
Acceptance rate 32%. Link
2017-05-03.The code of our paper "Unbiased shape compactness for
segmentation" has been made publicly available in GitHub.Link.
2017-04-17.Our paper "3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study"
has been accepted at NeuroImage. Link
2017-04-03.The code of our paper "3D fully convolutional networks for
subcortical segmentation in MRI: A large-scale study" has been released in GitHub.Link
2017-02-28. Our paper "DOPE: Distributed Optimization for Pairwise Energies" has
been accepted at CVPR 2017, Honolulu.
2017-02-21.We are hiring!!!! We have several interesting and fully funded PhD positions in deep
learning applied to medical image analysis. For further information, please visit this link.
2016-10-01. I have been invited as speaker at the summit "deep learning in healthcare"(https://www.re-work.co/events/deep-learning-health-boston-2017), which will be held in Boston on May 25-26th, 2017. There
I'll talk about Segmentation of Medical Images via Deep Learning Techniques: Current State-Of-The-Art and Perspectives.