Search Results for author: Pierre-Henri Conze

Found 14 papers, 1 papers with code

Multi-Task, Multi-Domain Deep Segmentation with Shared Representations and Contrastive Regularization for Sparse Pediatric Datasets

no code implementations21 May 2021 Arnaud Boutillon, Pierre-Henri Conze, Christelle Pons, Valérie Burdin, Bhushan Borotikar

Automatic segmentation of magnetic resonance (MR) images is crucial for morphological evaluation of the pediatric musculoskeletal system in clinical practice.

Multi-Structure Deep Segmentation with Shape Priors and Latent Adversarial Regularization

no code implementations25 Jan 2021 Arnaud Boutillon, Bhushan Borotikar, Christelle Pons, Valérie Burdin, Pierre-Henri Conze

Automatic segmentation of the musculoskeletal system in pediatric magnetic resonance (MR) images is a challenging but crucial task for morphological evaluation in clinical practice.

Efficient embedding network for 3D brain tumor segmentation

no code implementations22 Nov 2020 Hicham Messaoudi, Ahror Belaid, Mohamed Lamine Allaoui, Ahcene Zetout, Mohand Said Allili, Souhil Tliba, Douraied Ben Salem, Pierre-Henri Conze

As the input data is in 3D, the first layers of the encoder are devoted to the reduction of the third dimension in order to fit the input of the EfficientNet network.

Brain Tumor Segmentation Tumor Segmentation

Multi-structure bone segmentation in pediatric MR images with combined regularization from shape priors and adversarial network

no code implementations15 Sep 2020 Arnaud Boutillon, Bhushan Borotikar, Valérie Burdin, Pierre-Henri Conze

To overcome the scarcity and heterogeneity of pediatric datasets, we adopt a regularization strategy to improve the generalization of segmentation models.

CHAOS Challenge -- Combined (CT-MR) Healthy Abdominal Organ Segmentation

1 code implementation17 Jan 2020 A. Emre Kavur, N. Sinem Gezer, Mustafa Barış, Sinem Aslan, Pierre-Henri Conze, Vladimir Groza, Duc Duy Pham, Soumick Chatterjee, Philipp Ernst, Savaş Özkan, Bora Baydar, Dmitry Lachinov, Shuo Han, Josef Pauli, Fabian Isensee, Matthias Perkonigg, Rachana Sathish, Ronnie Rajan, Debdoot Sheet, Gurbandurdy Dovletov, Oliver Speck, Andreas Nürnberger, Klaus H. Maier-Hein, Gözde BOZDAĞI AKAR, Gözde Ünal, Oğuz Dicle, M. Alper Selver

The analysis shows that the performance of DL models for single modality (CT / MR) can show reliable volumetric analysis performance (DICE: 0. 98 $\pm$ 0. 00 / 0. 95 $\pm$ 0. 01) but the best MSSD performance remain limited (21. 89 $\pm$ 13. 94 / 20. 85 $\pm$ 10. 63 mm).

Combining Shape Priors with Conditional Adversarial Networks for Improved Scapula Segmentation in MR images

no code implementations20 Oct 2019 Arnaud Boutillon, Bhushan Borotikar, Valérie Burdin, Pierre-Henri Conze

This paper proposes an automatic method for scapula bone segmentation from Magnetic Resonance (MR) images using deep learning.

Automatic detection of rare pathologies in fundus photographs using few-shot learning

no code implementations22 Jul 2019 Gwenolé Quellec, Mathieu Lamard, Pierre-Henri Conze, Pascale Massin, Béatrice Cochener

This paper presents a new few-shot learning framework that extends convolutional neural networks (CNNs), trained for frequent conditions, with an unsupervised probabilistic model for rare condition detection.

One-Shot Learning Transfer Learning

Unsupervised learning-based long-term superpixel tracking

no code implementations25 Feb 2019 Pierre-Henri Conze, Florian Tilquin, Mathieu Lamard, Fabrice Heitz, Gwenolé Quellec

Finding correspondences between structural entities decomposing images is of high interest for computer vision applications.

Video Object Tracking

Healthy versus pathological learning transferability in shoulder muscle MRI segmentation using deep convolutional encoder-decoders

no code implementations6 Jan 2019 Pierre-Henri Conze, Sylvain Brochard, Valérie Burdin, Frances T. Sheehan, Christelle Pons

Methodological aspects are evaluated in a leave-one-out fashion on a dataset of 24 shoulder examinations from patients with obstetrical brachial plexus palsy and focus on 4 different muscles including deltoid as well as infraspinatus, supraspinatus and subscapularis from the rotator cuff.

MRI segmentation

Adaptive strategy for superpixel-based region-growing image segmentation

no code implementations17 Mar 2018 Mahaman Sani Chaibou, Pierre-Henri Conze, Karim Kalti, Basel Solaiman, Mohamed Ali Mahjoub

From an initial contour-constrained over-segmentation of the input image, the image segmentation is achieved by iteratively merging similar superpixels into regions.

BSDS500 Semantic Segmentation

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