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University of Strasbourg, France

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4 Papers

Angular Uncertainty Refinement and Image Reconstruction Improvement in Cryo-electron Tomography

Topics: Image Enhancement and Restoration; Early and Biologically-Inspired Vision; Medical Image Applications

Authors: Hmida Rojbani ¹ , Étienne Baudrier ² , Benoît Naegel ² , Loïc Mazo ² and Atef Hamouda ³

Affiliations: ¹ University of Strasbourg and University El-Manar, France , ² University of Strasbourg, France , ³ University El-Manar, Tunisia

Digital Object Identifier: 10.5220/0005680600940100

Proceedings of VISAPP 2016/VISIGRAPP, ISBN: 978-989-758-175-5

Quick Abstract

In the field of cryo-electron tomography (cryo-ET), numerous approaches have been proposed to tackle the difficulties of the three-dimensional reconstruction problem. And that, in order to cope with (1) the missing and noisy data from the collected projections, (2) errors in projection images due to acquisition problems, (3) the capacity of processing large data sets and parameterizing the contrast function of the electron microscopy. In this paper, we present a novel approach for dealing with angular uncertainty in cryo-ET. To accomplish this task we propose a cost function and with the use of the nonlinear version of the optimization algorithm called Conjugate Gradient, we minimize it. We test the efficiency of our algorithm with both simulated and real data.

Related Ontology Subjects/Areas/Topics (7)

Applications and Services	Image and Video Analysis	Image Formation and Preprocessing
Computer Vision, Visualization and Computer Graphics	Image Enhancement and Restoration	Medical Image Applications
Early and Biologically-Inspired Vision

A Fuzzy-Rule Based Ontology for Urban Object Recognition

Topics: Applications and Case-Studies; Domain Analysis and Modeling

Authors: Stella Marc-Zwecker , Khalid Asnoune and Cédric Wemmert

Affiliation: University of Strasbourg and CNRS, France

Digital Object Identifier: 10.5220/0005026601530160

Proceedings of KEOD 2014/IC3K, ISBN: 978-989-758-049-9

Quick Abstract

In this paper we outline the principles of a methodology for semi-automatic recognition of urban objects from satellite images. The methodology aims to provide a framework for bridging the semantic gap problem. Its principle consists in linking abstract geographical domain concepts with image segments, by the means of ontologies use. The imprecision of image data and of qualitative rules formulated by experts geographers are handled by fuzzy logic mechanisms. We have defined fuzzy rules, implemented in SWRL (Semantic Web Rule Language), which allow classification of image segments in the ontology. We propose some fuzzy classification strategies, which are compared and evaluated through an experimentation performed on a VHR image of Strasbourg region.

Related Ontology Subjects/Areas/Topics (6)

Applications and Case-studies		Domain Analysis and Modeling		Knowledge-Based Systems
Artificial Intelligence		Knowledge Engineering and Ontology Development		Symbolic Systems

Fast Segmentation for Texture-based Cartography of whole Slide Images

Topics: Segmentation and Grouping; Color and Texture Analyses; Medical Image Applications

Authors: Grégory Apou ¹ , Benoît Naegel ¹ , Germain Forestier ² , Friedrich Feuerhake ³ and Cédric Wemmert ¹

Affiliations: ¹ University of Strasbourg, France , ² University of Haute Alsace, France , ³ Hannover Medical School, Germany

Digital Object Identifier: 10.5220/0004687403090319

Proceedings of VISAPP 2014/VISIGRAPP, ISBN: 978-989-758-003-1

Quick Abstract

In recent years, new optical microscopes have been developed, providing very high spatial resolution images called Whole Slide Images (WSI). The fast and accurate display of such images for visual analysis by pathologists and the conventional automated analysis remain challenging, mainly due to the image size (sometimes billions of pixels) and the need to analyze certain image features at high resolution. To propose a decision support tool to help the pathologist interpret the information contained by the WSI, we present a new approach to establish an automatic cartography of WSI in reasonable time. The method is based on an original segmentation algorithm and on a supervised multiclass classification using a textural characterization of the regions computed by the segmentation. Application to breast cancer WSI shows promising results in terms of speed and quality.

Related Ontology Subjects/Areas/Topics (6)

Applications and Services		Computer Vision, Visualization and Computer Graphics		Medical Image Applications
Color and Texture Analyses		Image and Video Analysis		Segmentation and Grouping

MULTI-SEMANTIC APPROACH TOWARDS A GENERIC FORMAL SOLVER OF TOOL PLACEMENT FOR PERCUTANEOUS SURGERY

Topic: Intelligent Problem Solving

Authors: Caroline Essert-Villard , Claire Baegert and Pascal Schreck

Affiliation: Université de Strasbourg, France

Digital Object Identifier: 10.5220/0002303804430446

Proceedings of KEOD 2009/IC3K, ISBN: 978-989-674-012-2

Quick Abstract

In this paper, we study the multiple points of view when generalizing a method based on many criteria optimization, in the framework of percutaneous surgery planning. The aim of the prototype is to find an optimal position of surgical tools to help the surgeons in planning the intervention. We explain how, with a formal geometric solver and meta programming, we intend to build a modular tool, capable of being extended to new interventions, with few programming efforts.

Related Ontology Subjects/Areas/Topics (7)

Artificial Intelligence	Knowledge Engineering and Ontology Development	Software Engineering
Enterprise Software Technologies	Knowledge-Based Systems	Symbolic Systems
Intelligent Problem Solving

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