Live extraction of curvilinear structures from lidar raw data

International audienceIn this paper, a general framework is proposed for live extraction of curvilinear structures such as roads or ridges from airborne LiDAR raw data, in the scope of present and past man-environment interaction studies. Unlike most approaches in literature, classified ground points are directly processed here, rather than derived products such as digital terrain models (DTM). This allows to detect possible lacks of ground points due to LiDAR signal occlusions caused by dense coniferous canopies. An efficient and simple solution based on discrete geometry tools is described for supervised context in which the user just indicates where the extraction should take place. Fast response times are required to ensure a good man-system interaction. The framework performance is first evaluated on the example of the extraction of forest roads in a mountainous area, as these objects are well marked in the DTM and hence provide some kind of ground truth. Good execution time and accuracy level are reported. Then this framework is applied to the detection of prominent curvilinear structures, which are much more diffuse objects, but of greater interest than roads in the scope of the present project. Achieved results show high potential of the proposed approach to help archaeologists and geomorphologists in finding areas of interest for future prospection using LiDAR data

Extension des segments flous aux images en niveaux de gris pour l'extraction interactive de segments de droites

National audienceThe recognition of discrete straight segments is a significant topic in the field of discrete geometry and for many applications dealing with geometric feature extraction. It can be performed from noisy binary data using the concept of blurred segments [3,2]. However, to our best knowledge, these algorithms have never been defined to directly extract straight segments in gray level images. This article proposes a solution to extend the recognition by using gray level image information. Although initially intended to be implemented within a semi-automatic line selec- tion tool used in an interactive 3D modeling application, it also meets more general parameter extraction requirements.La reconnaissance de segments de droites discrètes est un problème significatif dans le domaine de la géométrie dis- crète et dans beaucoup d'applications d'extraction de pa- ramètres géométriques. L'utilisation du concept des seg- ments flous permet de traiter des images binaires brui- tées [3, 2]. Cependant ces algorithmes n'ont encore ja- mais été définis pour être utilisés directement dans des images en niveaux de gris. Nous proposons ici une solu- tion pour étendre la reconnaissance en utilisant les infor- mations des niveaux de gris d'une image. Bien qu'initia- lement conçu pour un outil semi-automatique de sélection de droites dans une application de modélisation 3d interac- tive, l'approche proposée répond aussi à des besoins plus généraux liés à l'extraction de paramètres

Automatic forest road extraction from LiDAR data of mountainous areas

International audienceIn this paper, a framework is proposed to extract forest roads from LiDAR (Light Detection and Ranging) data in mountainous areas. For that purpose, an efficient and simple solution based on discrete geometry and mathematical morphology tools is proposed. The framework is composed of two steps: (i) detecting road candidates in DTM (Digital Terrain Model) views using a mathematical morphology filter and a fast blurred segment detector in order to select a set of road seeds; (ii) extracting road sections from the obtained seeds using only the raw LiDAR points to cope with DTM approximations. For the second step, a previous tool for fast extraction of linear structures directly from ground points was adapted to automatically process each seed. It first performs a recognition of the road structure under the seed. In case of success, the structure is tracked and extended as far as possible on each side of the segment before post-processing validation and cleaning. Experiments on real data over a wide mountain area (about 78 km^2) have been conducted to validate the proposed method

Editorial Hommage à Pierre Vrignaud

Notre collègue, Pierre Vrignaud, professeur émérite de psychologie de l’orientation est décédé le dimanche 29 avril 2018. Après des études en langues orientales et en psychologie, il a débuté en 1975 sa carrière comme conseiller d’orientation en région parisienne, puis a rejoint en 1986 le service de formation des conseillers d’orientation de l’Inetop-Cnam. Passionné de recherche, il intègre en 1990 le service de recherche de ce même institut, soutient sa thèse de doctorat en 1999 et son habi..

Complementary Experiments of the Thick Line Segment Detection Algorithm: Evaluation of ADS and ATC Concepts

This document presents complementary experiments on the published algorithm of Thick Line Segment Detection with Fast Directional Tracking. The main paper is actually published at ICIAP 2019 [2]. First tests compare the performance of the detector with and without adaptive directional scans (ADS) and assigned thickness control (ATC). On the detector without ADS, the ne tracking step must be performed twice to get less risk of growing blurred segment escape from the scan strip

Ab initio calculation of effective work functions for a TiN/HfO(2)/SiO(2)/Si transistor stack

International audienceClose Ab initio techniques are used to calculate the effective work function (Weff) of a TiN/HfO2/SiO2/Si stack representing a metal-oxide-semiconductor (MOS) transistor gate taking into account first order many body effects. The required band offsets were calculated at each interface varying its composition. Finally, the transitivity of local density approximation (LDA) calculated bulk band lineups were used and completed by many body perturbation theory (MBPT) bulk corrections for the terminating materials (Si and TiN) of the MOS stack. With these corrections the ab initio calculations predict a Weff of a TiN metal gate on HfO2 to be close to 5.0 eV

The modelling system PYRAMIDE as an interactive help for the guidance of the inspection vehicle CENTAURE

Disponible dans les fichiers attachés à ce documen

Impact of SBRT fractionation in hypoxia dose painting - Accounting for heterogeneous and dynamic tumor oxygenation

Purpose Tumor hypoxia, often found in nonsmall cell lung cancer (NSCLC), implies an increased resistance to radiotherapy. Pretreatment assessment of tumor oxygenation is, therefore, warranted in these patients, as functional imaging of hypoxia could be used as a basis for dose painting. This study aimed at investigating the feasibility of using a method for calculating the dose required in hypoxic subvolumes segmented on F-18-HX4 positron emission tomography (PET) imaging of NSCLC. Methods Positron emission tomography imaging data based on the hypoxia tracer F-18-HX4 of 19 NSCLC patients were included in the study. Normalized tracer uptake was converted to oxygen partial pressure (pO(2)) and hypoxic target volumes (HTVs) were segmented using a threshold of 10 mmHg. Uniform doses required to overcome the hypoxic resistance in the target volumes were calculated based on a previously proposed method taking into account the effect of interfraction reoxygenation, for fractionation schedules ranging from extremely hypofractionated stereotactic body radiotherapy (SBRT) to conventionally fractionated radiotherapy. Results Gross target volumes ranged between 6.2 and 859.6 cm(3), and the hypoxic fraction <10 mmHg between 1.2% and 72.4%. The calculated doses for overcoming the resistance of cells in the HTVs were comparable to those currently prescribed in clinical practice as well as those previously tested in feasibility studies on dose escalation in NSCLC. Depending on the size of the HTV and the distribution of pO(2), HTV doses were calculated as 43.6-48.4 Gy for a three-fraction schedule, 51.7-57.6 Gy for five fractions, and 59.5-66.4 Gy for eight fractions. For patients in whom the HTV pO(2) distribution was more favorable, a lower dose was required despite a bigger volume. Tumor control probability was lower for single-fraction schedules, while higher levels of tumor control probability were found for schedules employing several fractions. Conclusions The method to account for heterogeneous and dynamic hypoxia in target volume segmentation and dose prescription based on F-18-HX4-PET imaging appears feasible in NSCLC patients. The distribution of oxygen partial pressure within HTV could impact the required prescribed dose more than the size of the volume

Фінансовий контролінг як інструмент управління діяльністю суб'єкта господарювання

PURPOSE: Multiple imaging techniques are nowadays available for clinical in-vivo visualization of tumour biology. FDG PET/CT identifies increased tumour metabolism, hypoxia PET visualizes tumour oxygenation and dynamic contrast-enhanced (DCE) CT characterizes vasculature and morphology. We explored the relationships among these biological features in patients with non-small-cell lung cancer (NSCLC) at both the patient level and the tumour subvolume level. METHODS: A group of 14 NSCLC patients from two ongoing clinical trials (NCT01024829 and NCT01210378) were scanned using FDG PET/CT, HX4 PET/CT and DCE CT prior to chemoradiotherapy. Standardized uptake values (SUV) in the primary tumour were calculated for the FDG and hypoxia HX4 PET/CT scans. For hypoxia imaging, the hypoxic volume, fraction and tumour-to-blood ratio (TBR) were also defined. Blood flow and blood volume were obtained from DCE CT imaging. A tumour subvolume analysis was used to quantify the spatial overlap between subvolumes. RESULTS: At the patient level, negative correlations were observed between blood flow and the hypoxia parameters (TBR >1.2): hypoxic volume (−0.65, p = 0.014), hypoxic fraction (−0.60, p = 0.025) and TBR (−0.56, p = 0.042). At the tumour subvolume level, hypoxic and metabolically active subvolumes showed an overlap of 53 ± 36 %. Overlap between hypoxic sub-volumes and those with high blood flow and blood volume was smaller: 15 ± 17 % and 28 ± 28 %, respectively. Half of the patients showed a spatial mismatch (overlap <5 %) between increased blood flow and hypoxia. CONCLUSION: The biological imaging features defined in NSCLC tumours showed large interpatient and intratumour variability. There was overlap between hypoxic and metabolically active subvolumes in the majority of tumours, there was spatial mismatch between regions with high blood flow and those with increased hypoxia. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00259-015-3169-4) contains supplementary material, which is available to authorized users