Search Results for author: Lisa Di Jorio

Found 8 papers, 0 papers with code

Application of Homomorphic Encryption in Medical Imaging

no code implementations12 Oct 2021 Francis Dutil, Alexandre See, Lisa Di Jorio, Florent Chandelier

In this technical report, we explore the use of homomorphic encryption (HE) in the context of training and predicting with deep learning (DL) models to deliver strict \textit{Privacy by Design} services, and to enforce a zero-trust model of data governance.

Federated Learning

Precision-Weighted Federated Learning

no code implementations20 Jul 2021 Jonatan Reyes, Lisa Di Jorio, Cecile Low-Kam, Marta Kersten-Oertel

Our performance evaluations show 9% better predictions with MNIST, 18% with Fashion-MNIST, and 5% with CIFAR-10 in the non-IID setting.

Federated Learning Image Classification

Cross-Modal Information Maximization for Medical Imaging: CMIM

no code implementations20 Oct 2020 Tristan Sylvain, Francis Dutil, Tess Berthier, Lisa Di Jorio, Margaux Luck, Devon Hjelm, Yoshua Bengio

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.)

Image Classification Medical Image Classification +1

Learn Faster and Forget Slower via Fast and Stable Task Adaptation

no code implementations2 Jul 2020 Farshid Varno, Lucas May Petry, Lisa Di Jorio, Stan Matwin

We empirically show that compared to prevailing fine-tuning practices, FAST learns the target task faster and forgets the source task slower.

Transfer Learning

Efficient Neural Task Adaptation by Maximum Entropy Initialization

no code implementations25 May 2019 Farshid Varno, Behrouz Haji Soleimani, Marzie Saghayi, Lisa Di Jorio, Stan Matwin

Transferring knowledge from one neural network to another has been shown to be helpful for learning tasks with few training examples.

Transfer Learning

InfoMask: Masked Variational Latent Representation to Localize Chest Disease

no code implementations28 Mar 2019 Saeid Asgari Taghanaki, Mohammad Havaei, Tess Berthier, Francis Dutil, Lisa Di Jorio, Ghassan Hamarneh, Yoshua Bengio

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.

Multiple Instance Learning

Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation

no code implementations16 Feb 2017 Michal Drozdzal, Gabriel Chartrand, Eugene Vorontsov, Lisa Di Jorio, An Tang, Adriana Romero, Yoshua Bengio, Chris Pal, Samuel Kadoury

Moreover, when applying our 2D pipeline on a challenging 3D MRI prostate segmentation challenge we reach results that are competitive even when compared to 3D methods.

Image Segmentation Medical Image Segmentation +2

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