Edwin Carlinet

In Mathematical morphology and its application to signal and image processing – proceedings of the 14th international symposium on mathematical morphology (ISMM)

Abstract The component trees provide a high-level, hierarchical, and contrast invariant representations of images, suitable for many image processing tasks. Yet their definition is ill-formed on multivariate data, e.g., color images, multi-modality images, multi-band images, and so on. Common workarounds such as marginal processing, or imposing a total order on data are not satisfactory and yield many problems, such as artifacts, loss of invariances, etc. In this paper, inspired by the way the Multivariate Tree of Shapes (MToS) has been defined, we propose a definition for a Multivariate min-tree or max-tree.

Spherical fluorescent particle segmentation and tracking in 3D confocal microscopy

By Élodie Puybareau, Edwin Carlinet, Alessandro Benfenati, Hugues Talbot

2019-03-13

In Mathematical morphology and its application to signal and image processing – proceedings of the 14th international symposium on mathematical morphology (ISMM)

Abstract Spherical fluorescent particle are micrometer-scale spherical beads used in various areas of physics, chemistry or biology as markers associated with local physical media. They are useful for example in fluid dynamics to characterize flows, diffusion coefficients, viscosity or temperature; they are used in cells dynamics to estimate mechanical strain and stress at the micrometer scale. In order to estimate these physical measurements, tracking these particles is necessary. Numerous approaches and existing packages, both open-source and proprietary are available to achieve tracking with a high degree of precision in 2D.

Intervertebral disc segmentation using mathematical morphology—A CNN-free approach

By Edwin Carlinet, Thierry Géraud

2018-11-26

In Proceedings of the 5th MICCAI workshop & challenge on computational methods and clinical applications for spine imaging (CSI)

Abstract In the context of the challenge of “automatic InterVertebral Disc (IVD) localization and segmentation from 3D multi-modality MR images” that took place at MICCAI 2018, we have proposed a segmentation method based on simple image processing operators. Most of these operators come from the mathematical morphology framework. Driven by some prior knowledge on IVDs (basic information about their shape and the distance between them), and on their contrast in the different modalities, we were able to segment correctly almost every IVD.

An image processing library in modern C++: Getting simplicity and efficiency with generic programming

By Michaël Roynard, Edwin Carlinet, Thierry Géraud

2018-10-25

In Proceedings of the 2nd workshop on reproducible research in pattern recognition (RRPR 2018)

Abstract As there are as many clients as many usages of an Image Processing library, each one may expect different services from it. Some clients may look for efficient and production-quality algorithms, some may look for a large tool set, while others may look for extensibility and genericity to inter-operate with their own code base… but in most cases, they want a simple-to-use and stable product. For a C++ Image Processing library designer, it is difficult to conciliate genericity, efficiency and simplicity at the same time.

Left atrial segmentation in a few seconds using fully convolutional network and transfer learning

By Élodie Puybareau, Zhou Zhao, Younes Khoudli, Edwin Carlinet, Yongchao Xu, Jérôme Lacotte, Thierry Géraud

2018-10-25

In Proceedings of the workshop on statistical atlases and computational modelling of the heart (STACOM 2018), in conjunction with MICCAI

Abstract In this paper, we propose a fast automatic method that segments left atrial cavity from 3D GE-MRIs without any manual assistance, using a fully convolutional network (FCN) and transfer learning. This FCN is the base network of VGG-16, pre-trained on ImageNet for natural image classification, and fine tuned with the training dataset of the MICCAI 2018 Atrial Segmentation Challenge. It relies on the “pseudo-3D” method published at ICIP 2017, which allows for segmenting objects from 2D color images which contain 3D information of MRI volumes.

The tree of shapes turned into a max-tree: A simple and efficient linear algorithm

By Edwin Carlinet, Thierry Géraud, Sébastien Crozet

2018-05-10

In Proceedings of the 24th IEEE international conference on image processing (ICIP)

Abstract The Tree of Shapes (ToS) is a morphological tree-based representation of an image translating the inclusion of its level lines. It features many invariances to image changes, which makes it well-suited for a lot of applications in image processing and pattern recognition. In this paper, we propose a way of turning this algorithm into a Max-Tree computation. The latter has been widely studied, and many efficient algorithms (including parallel ones) have been developed.

Un algorithme de complexité linéaire pour le calcul de l’arbre des formes

By Edwin Carlinet, Sébastien Crozet, Thierry Géraud

2018-05-04

In Actes du congrès reconnaissance des formes, image, apprentissage et perception (RFIAP)

Abstract L’arbre des formes (AdF) est une représentation morpho- logique hiérarchique de l’image qui traduit l’inclusion des ses lignes de niveaux. Il se caractérise par son invariance à certains changement de l’image, ce qui fait de lui un outil idéal pour le développement d’applications de reconnaissance des formes. Dans cet article, nous proposons une méthode pour transformer sa construction en un calcul de Max-tree. Ce dernier a été largement étudié au cours des dernières années et des algorithmes efficaces (dont certains parallèles) existent déjà.

La pseudo-distance du dahu

By Edwin Carlinet, Yongchao Xu, Nicolas Boutry, Thierry Géraud

2017-03-21

In Actes d’ORASIS

Abstract La distance de la barrière minimum est définie comme le plus petit intervalle de l’ensemble des niveaux de gris le long d’un chemin entre deux points dans une image. Pour cela, on considère que l’image est un graphe à valeurs sur les sommets. Cependant, cette définition ne correspond pas à l’interprétation d’une image comme étant une carte d’élévation, c’est-à-dire, un paysage continu d’une manière ou d’une autre. En se plaçant dans le cadre des fonctions multivoques, nous présentons une nouvelle définition pour cette distance.

Introducing the Dahu pseudo-distance

By Thierry Géraud, Yongchao Xu, Edwin Carlinet, Nicolas Boutry

2017-02-23

In Mathematical morphology and its application to signal and image processing – proceedings of the 13th international symposium on mathematical morphology (ISMM)

Abstract The minimum barrier (MB) distance is defined as the minimal interval of gray-level values in an image along a path between two points, where the image is considered as a vertex-valued graph. Yet this definition does not fit with the interpretation of an image as an elevation map, i.e. a somehow continuous landscape. In this paper, based on the discrete set-valued continuity setting, we present a new discrete definition for this distance, which is compatible with this interpretation, while being free from digital topology issues.

Region-based classification of remote sensing images with the morphological tree of shapes

By Gabriele Cavallaro, Mauro Dalla Mura, Edwin Carlinet, Thierry Géraud, Nicola Falco, Jón Atli Benediktsson

2016-04-12

In Proceedings of the IEEE international geoscience and remote sensing symposium (IGARSS)

Abstract Satellite image classification is a key task used in remote sensing for the automatic interpretation of a large amount of information. Today there exist many types of classification algorithms using advanced image processing methods enhancing the classification accuracy rate. One of the best state-of-the-art methods which improves significantly the classification of complex scenes relies on Self-Dual Attribute Profiles (SDAPs). In this approach, the underlying representation of an image is the Tree of Shapes, which encodes the inclusion of connected components of the image.

Introducing multivariate connected openings and closings

Spherical fluorescent particle segmentation and tracking in 3D confocal microscopy

Intervertebral disc segmentation using mathematical morphology—A CNN-free approach

An image processing library in modern C++: Getting simplicity and efficiency with generic programming

Left atrial segmentation in a few seconds using fully convolutional network and transfer learning

The tree of shapes turned into a max-tree: A simple and efficient linear algorithm

Un algorithme de complexité linéaire pour le calcul de l’arbre des formes

La pseudo-distance du dahu

Introducing the Dahu pseudo-distance

Region-based classification of remote sensing images with the morphological tree of shapes

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