Search Results for author: Christian Desrosiers

Found 44 papers, 17 papers with code

Diversified Multi-prototype Representation for Semi-supervised Segmentation

no code implementations16 Nov 2021 Jizong Peng, Christian Desrosiers, Marco Pedersoli

This work considers semi-supervised segmentation as a dense prediction problem based on prototype vector correlation and proposes a simple way to represent each segmentation class with multiple prototypes.

Mixed-supervised segmentation: Confidence maximization helps knowledge distillation

1 code implementation21 Sep 2021 Bingyuan Liu, Christian Desrosiers, Ismail Ben Ayed, Jose Dolz

In this work, we propose a dual-branch architecture, where the upper branch (teacher) receives strong annotations, while the bottom one (student) is driven by limited supervision and guided by the upper branch.

Knowledge Distillation Medical Image Segmentation +1

Trust your neighbors: A comprehensive survey of neighborhood-based methods for recommender systems

no code implementations9 Sep 2021 Athanasios N. Nikolakopoulos, Xia Ning, Christian Desrosiers, George Karypis

Collaborative recommendation approaches based on nearest-neighbors are still highly popular today due to their simplicity, their efficiency, and their ability to produce accurate and personalized recommendations.

Recommendation Systems

Manifold-aware Synthesis of High-resolution Diffusion from Structural Imaging

no code implementations9 Aug 2021 Benoit Anctil-Robitaille, Antoine Théberge, Pierre-Marc Jodoin, Maxime Descoteaux, Christian Desrosiers, Hervé Lombaert

The physical and clinical constraints surrounding diffusion-weighted imaging (DWI) often limit the spatial resolution of the produced images to voxels up to 8 times larger than those of T1w images.

Context-aware virtual adversarial training for anatomically-plausible segmentation

no code implementations12 Jul 2021 Ping Wang, Jizong Peng, Marco Pedersoli, Yuanfeng Zhou, Caiming Zhang, Christian Desrosiers

Despite their outstanding accuracy, semi-supervised segmentation methods based on deep neural networks can still yield predictions that are considered anatomically impossible by clinicians, for instance, containing holes or disconnected regions.

Efficient Pairwise Neuroimage Analysis using the Soft Jaccard Index and 3D Keypoint Sets

1 code implementation11 Mar 2021 Laurent Chauvin, Kuldeep Kumar, Christian Desrosiers, William Wells III, Matthew Toews

Our measure generalizes the Jaccard index to account for soft set equivalence (SSE) between keypoint elements, via an adaptive kernel framework modeling uncertainty in keypoint appearance and geometry.

Boosting Semi-supervised Image Segmentation with Global and Local Mutual Information Regularization

1 code implementation8 Mar 2021 Jizong Peng, Marco Pedersoli, Christian Desrosiers

In this method, we maximize the MI for intermediate feature embeddings that are taken from both the encoder and decoder of a segmentation network.

Medical Image Segmentation Semantic Segmentation

Teach me to segment with mixed supervision: Confident students become masters

1 code implementation15 Dec 2020 Jose Dolz, Christian Desrosiers, Ismail Ben Ayed

In conjunction with a standard cross-entropy over the labeled pixels, our novel formulation integrates two important terms: (i) a Shannon entropy loss defined over the less-supervised images, which encourages confident student predictions at the bottom branch; and (ii) a Kullback-Leibler (KL) divergence, which transfers the knowledge from the predictions generated by the strongly supervised branch to the less-supervised branch, and guides the entropy (student-confidence) term to avoid trivial solutions.

Semantic Segmentation

Privacy Preserving for Medical Image Analysis via Non-Linear Deformation Proxy

no code implementations25 Nov 2020 Bach Ngoc Kim, Jose Dolz, Christian Desrosiers, Pierre-Marc Jodoin

Results show that the segmentation accuracy of our method is similar to a system trained on non-encoded images, while considerably reducing the ability to recover subject identity.

Brain Segmentation

Self-paced and self-consistent co-training for semi-supervised image segmentation

1 code implementation31 Oct 2020 Ping Wang, Jizong Peng, Marco Pedersoli, Yuanfeng Zhou, Caiming Zhang, Christian Desrosiers

Moreover, to encourage predictions from different networks to be both consistent and confident, we enhance this generalized JSD loss with an uncertainty regularizer based on entropy.

Semantic Segmentation

Machine learning for the diagnosis of Parkinson's disease: A systematic review

1 code implementation13 Oct 2020 Jie Mei, Christian Desrosiers, Johannes Frasnelli

Diagnosis of Parkinson's disease (PD) is commonly based on medical observations and assessment of clinical signs, including the characterization of a variety of motor symptoms.

Decision Making

Realistic Image Normalization for Multi-Domain Segmentation

1 code implementation29 Sep 2020 Pierre-Luc Delisle, Benoit Anctil-Robitaille, Christian Desrosiers, Herve Lombaert

This paper proposes to revisit the conventional image normalization approach by instead learning a common normalizing function across multiple datasets.

Semantic Segmentation

Manifold-Aware CycleGAN for High-Resolution Structural-to-DTI Synthesis

no code implementations1 Apr 2020 Benoit Anctil-Robitaille, Christian Desrosiers, Herve Lombaert

To ensure that the generated diffusion tensors lie on the SPD(3) manifold, we exploit the theoretical properties of the exponential and logarithm maps of the Log-Euclidean metric.

Image-to-Image Translation

Adversarial normalization for multi domain image segmentation

no code implementations2 Dec 2019 Pierre-Luc Delisle, Benoit Anctil-Robitaille, Christian Desrosiers, Herve Lombaert

To solve this problem, we propose an adversarial normalization approach for image segmentation which learns common normalizing functions across multiple datasets while retaining image realism.

Semantic Segmentation

Learnable Pooling in Graph Convolution Networks for Brain Surface Analysis

no code implementations22 Nov 2019 Karthik Gopinath, Christian Desrosiers, Herve Lombaert

This paper proposes a new learnable graph pooling method for processing multiple surface-valued data to output subject-based information.

General Classification

Deep radiomic features from MRI scans predict survival outcome of recurrent glioblastoma

no code implementations15 Nov 2019 Ahmad Chaddad, Saima Rathore, Mingli Zhang, Christian Desrosiers, Tamim Niazi

This paper proposes to use deep radiomic features (DRFs) from a convolutional neural network (CNN) to model fine-grained texture signatures in the radiomic analysis of recurrent glioblastoma (rGBM).

General Classification

Information based Deep Clustering: An experimental study

no code implementations3 Oct 2019 Jizong Peng, Christian Desrosiers, Marco Pedersoli

The second, named Invariant Information Clustering (IIC), maximizes the mutual information between the clustering of a sample and its geometrically transformed version.

Deep Clustering

Boosting Image Recognition with Non-differentiable Constraints

no code implementations2 Oct 2019 Xuan Li, Yuchen Lu, Peng Xu, Jizong Peng, Christian Desrosiers, Xue Liu

In this paper, we study the problem of image recognition with non-differentiable constraints.

Privacy-Net: An Adversarial Approach for Identity-Obfuscated Segmentation of Medical Images

no code implementations9 Sep 2019 Bach Ngoc Kim, Jose Dolz, Pierre-Marc Jodoin, Christian Desrosiers

Our novel architecture is composed of three components: 1) an encoder network which removes identity-specific features from input medical images, 2) a discriminator network that attempts to identify the subject from the encoded images, 3) a medical image analysis network which analyzes the content of the encoded images (segmentation in our case).

Revisiting CycleGAN for semi-supervised segmentation

1 code implementation30 Aug 2019 Arnab Kumar Mondal, Aniket Agarwal, Jose Dolz, Christian Desrosiers

In this work, we study the problem of training deep networks for semantic image segmentation using only a fraction of annotated images, which may significantly reduce human annotation efforts.

Semantic Segmentation Style Transfer

Constrained Deep Networks: Lagrangian Optimization via Log-Barrier Extensions

1 code implementation8 Apr 2019 Hoel Kervadec, Jose Dolz, Jing Yuan, Christian Desrosiers, Eric Granger, Ismail Ben Ayed

While sub-optimality is not guaranteed for non-convex problems, this result shows that log-barrier extensions are a principled way to approximate Lagrangian optimization for constrained CNNs via implicit dual variables.

Semantic Segmentation Stochastic Optimization +1

Deep Co-Training for Semi-Supervised Image Segmentation

2 code implementations27 Mar 2019 Jizong Peng, Guillermo Estrada, Marco Pedersoli, Christian Desrosiers

In this paper, we aim to improve the performance of semantic image segmentation in a semi-supervised setting in which training is effectuated with a reduced set of annotated images and additional non-annotated images.

Semantic Segmentation

IVD-Net: Intervertebral disc localization and segmentation in MRI with a multi-modal UNet

1 code implementation19 Nov 2018 Jose Dolz, Christian Desrosiers, Ismail Ben Ayed

Despite the technological advances in medical imaging, IVD localization and segmentation are still manually performed, which is time-consuming and prone to errors.

Medical Image Segmentation

Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning

1 code implementation29 Oct 2018 Arnab Kumar Mondal, Jose Dolz, Christian Desrosiers

In addition, our work presents a comprehensive analysis of different GAN architectures for semi-supervised segmentation, showing recent techniques like feature matching to yield a higher performance than conventional adversarial training approaches.

3D Medical Imaging Segmentation Brain Image Segmentation +3

Dense Multi-path U-Net for Ischemic Stroke Lesion Segmentation in Multiple Image Modalities

no code implementations16 Oct 2018 Jose Dolz, Ismail Ben Ayed, Christian Desrosiers

First, instead of combining the available image modalities at the input, each of them is processed in a different path to better exploit their unique information.

Ischemic Stroke Lesion Segmentation Lesion Segmentation

Multi-region segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks

no code implementations28 May 2018 Jose Dolz, Xiaopan Xu, Jerome Rony, Jing Yuan, Yang Liu, Eric Granger, Christian Desrosiers, Xi Zhang, Ismail Ben Ayed, Hongbing Lu

Precise segmentation of bladder walls and tumor regions is an essential step towards non-invasive identification of tumor stage and grade, which is critical for treatment decision and prognosis of patients with bladder cancer (BC).

White matter fiber analysis using kernel dictionary learning and sparsity priors

no code implementations15 Apr 2018 Kuldeep Kumar, Kaleem Siddiqi, Christian Desrosiers

Results highlight the ability of our method to group streamlines into plausible bundles and illustrate the impact of sparsity priors on the performance of the proposed methods.

Dictionary Learning

HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation

3 code implementations9 Apr 2018 Jose Dolz, Karthik Gopinath, Jing Yuan, Herve Lombaert, Christian Desrosiers, Ismail Ben Ayed

Therefore, the proposed network has total freedom to learn more complex combinations between the modalities, within and in-between all the levels of abstraction, which increases significantly the learning representation.

Brain Segmentation Image Classification +3

Graph Convolutions on Spectral Embeddings: Learning of Cortical Surface Data

no code implementations27 Mar 2018 Karthik Gopinath, Christian Desrosiers, Herve Lombaert

This paper presents a novel approach for learning and exploiting surface data directly across surface domains.

Graph Matching

Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation

1 code implementation14 Dec 2017 Jose Dolz, Christian Desrosiers, Li Wang, Jing Yuan, Dinggang Shen, Ismail Ben Ayed

We report evaluations of our method on the public data of the MICCAI iSEG-2017 Challenge on 6-month infant brain MRI segmentation, and show very competitive results among 21 teams, ranking first or second in most metrics.

Infant Brain Mri Segmentation MRI segmentation +1

Modeling Information Flow Through Deep Neural Networks

no code implementations29 Nov 2017 Ahmad Chaddad, Behnaz Naisiri, Marco Pedersoli, Eric Granger, Christian Desrosiers, Matthew Toews

This paper proposes a principled information theoretic analysis of classification for deep neural network structures, e. g. convolutional neural networks (CNN).

Classification General Classification +1

Isointense Infant Brain Segmentation with a Hyper-dense Connected Convolutional Neural Network

1 code implementation16 Oct 2017 Jose Dolz, Ismail Ben Ayed, Jing Yuan, Christian Desrosiers

Neonatal brain segmentation in magnetic resonance (MR) is a challenging problem due to poor image quality and low contrast between white and gray matter regions.

Brain Segmentation Infant Brain Mri Segmentation +1

Multi-modal analysis of genetically-related subjects using SIFT descriptors in brain MRI

no code implementations18 Sep 2017 Kuldeep Kumar, Laurent Chauvin, Mathew Toews, Olivier Colliot, Christian Desrosiers

So far, fingerprinting studies have focused on identifying features from single-modality MRI data, which capture individual characteristics in terms of brain structure, function, or white matter microstructure.

White Matter Fiber Segmentation Using Functional Varifolds

no code implementations18 Sep 2017 Kuldeep Kumar, Pietro Gori, Benjamin Charlier, Stanley Durrleman, Olivier Colliot, Christian Desrosiers

We use it to cluster fibers with a dictionary learning and sparse coding-based framework, and present a preliminary analysis using HCP data.

Dictionary Learning

Unbiased Shape Compactness for Segmentation

1 code implementation28 Apr 2017 Jose Dolz, Ismail Ben Ayed, Christian Desrosiers

We propose to constrain segmentation functionals with a dimensionless, unbiased and position-independent shape compactness prior, which we solve efficiently with an alternating direction method of multipliers (ADMM).

A 3D fully convolutional neural network and a random walker to segment the esophagus in CT

no code implementations21 Apr 2017 Tobias Fechter, Sonja Adebahr, Dimos Baltas, Ismail Ben Ayed, Christian Desrosiers, Jose Dolz

These figures translate into a very good agreement with the reference contours and an increase in accuracy compared to other methods.

DOPE: Distributed Optimization for Pairwise Energies

no code implementations CVPR 2017 Jose Dolz, Ismail Ben Ayed, Christian Desrosiers

We formulate an Alternating Direction Method of Mul-tipliers (ADMM) that systematically distributes the computations of any technique for optimizing pairwise functions, including non-submodular potentials.

Distributed Optimization

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