414 research outputs found
4-D Gradient Vector Flow : segmentation par surface active pour images multi-composantes
National audienceDans cet article, nous généralisons le flux de vecteurs gradients à la segmentation par surface active d'images 3-D à valeurs vectorielles. Nous basons notre méthode sur la définition d'un tenseur de structure multi-composantes pondéré exploitant l'intégralité de l'information de l'image pour réduire la sensibilité au bruit et améliorer la précision du modèle. Appliquée à la segmentation de volumes biologiques en imagerie par tomographie d'émission de positrons (TEP) dynamique, nous validons notre méthode sur des simulations Monte Carlo réalistes d'images TEP de fantômes numériques
Membrane patterned by pulsed laser micromachining for proton exchange membrane fuel cell with sputtered ultra-low catalyst loadings
International audienceProton exchange membranes were nano-and micro-patterned on their cathode side by pressing them against stainless steel molds previously irradiated by a Ti:Sapphire femtosecond laser. The membranes were associated to ultra-low loaded thin catalytic layers (25 µgPt cm-2) prepared by plasma magnetron sputtering. The Pt catalyst was sputtered either on the membrane or on the porous electrode. The fuel cell performance in dry conditions were found to be highly dependent on the morphology of the membrane surface. When nanometric ripples covered by a Pt catalyst were introduced on the surface of the membrane, the fuel cell outperformed the conventional one with a flat membrane. By combining nano-and micro-patterns (nanometric ripples and 11-24 µm deep craters), the performance of the cells was clearly enhanced. The maximum power density achieved by the fuel cell was multiplied by a factor of 3.6 (at 50 °C and 3 bars): 438 mW cm-2 vs 122 mW cm-2. This improvement is due to high catalyst utilization with a high membrane conductivity. When Pt is sputtered on the porous electrode (and not on the membrane), the contribution of the patterned membrane to the fuel cell efficiency was less significant, except in the presence of nanometric ripples. This result suggests that the patterning of the membrane must be consistent with the way the catalyst is synthesized, on the membrane or on the porous electrode
GATE : a simulation toolkit for PET and SPECT
Monte Carlo simulation is an essential tool in emission tomography that can
assist in the design of new medical imaging devices, the optimization of
acquisition protocols, and the development or assessment of image
reconstruction algorithms and correction techniques. GATE, the Geant4
Application for Tomographic Emission, encapsulates the Geant4 libraries to
achieve a modular, versatile, scripted simulation toolkit adapted to the field
of nuclear medicine. In particular, GATE allows the description of
time-dependent phenomena such as source or detector movement, and source decay
kinetics. This feature makes it possible to simulate time curves under
realistic acquisition conditions and to test dynamic reconstruction algorithms.
A public release of GATE licensed under the GNU Lesser General Public License
can be downloaded at the address http://www-lphe.epfl.ch/GATE/
Validation of a small-animal PET simulation using GAMOS: a Geant4-based framework
onte Carlo-based modelling is a powerful tool to help in the design and optimization of positron emission tomography (PET) systems. The performance of these systems depends on several parameters, such as detector physical characteristics, shielding or electronics, whose effects can be studied on the basis of realistic simulated data. The aim of this paper is to validate a comprehensive study of the Raytest ClearPET small-animal PET scanner using a new Monte Carlo simulation platform which has been developed at CIEMAT (Madrid, Spain), called GAMOS (GEANT4-based Architecture for Medicine-Oriented Simulations). This toolkit, based on the GEANT4 code, was originally designed to cover multiple applications in the field of medical physics from radiotherapy to nuclear medicine, but has since been applied by some of its users in other fields of physics, such as neutron shielding, space physics, high energy physics, etc. Our simulation model includes the relevant characteristics of the ClearPET system, namely, the double layer of scintillator crystals in phoswich configuration, the rotating gantry, the presence of intrinsic radioactivity in the crystals or the storage of single events for an off-line coincidence sorting. Simulated results are contrasted with experimental acquisitions including studies of spatial resolution, sensitivity, scatter fraction and count rates in accordance with the National Electrical Manufacturers Association (NEMA) NU 4-2008 protocol. Spatial resolution results showed a discrepancy between simulated and measured values equal to 8.4% (with a maximum FWHM difference over all measurement directions of 0.5 mm). Sensitivity results differ less than 1% for a 250–750 keV energy window. Simulated and measured count rates agree well within a wide range of activities, including under electronic saturation of the system (the measured peak of total coincidences, for the mouse-sized phantom, was 250.8 kcps reached at 0.95 MBq mL−1 and the simulated peak was 247.1 kcps at 0.87 MBq mL−1). Agreement better than 3% was obtained in the scatter fraction comparison study. We also measured and simulated a mini-Derenzo phantom obtaining images with similar quality using iterative reconstruction methods. We concluded that the overall performance of the simulation showed good agreement with the measured results and validates the GAMOS package for PET applications. Furthermore, its ease of use and flexibility recommends it as an excellent tool to optimize design features or image reconstruction techniques
Psychophysiological effects of a web-based stress management system: A prospective, randomized controlled intervention study of IT and media workers [ISRCTN54254861]
BACKGROUND: The aim of the present study was to assess possible effects on mental and physical well-being and stress-related biological markers of a web-based health promotion tool. METHODS: A randomized, prospectively controlled study was conducted with before and after measurements, involving 303 employees (187 men and 116 women, age 23–64) from four information technology and two media companies. Half of the participants were offered web-based health promotion and stress management training (intervention) lasting for six months. All other participants constituted the reference group. Different biological markers were measured to detect possible physiological changes. RESULTS: After six months the intervention group had improved statistically significantly compared to the reference group on ratings of ability to manage stress, sleep quality, mental energy, concentration ability and social support. The anabolic hormone dehydroepiandosterone sulphate (DHEA-S) decreased significantly in the reference group as compared to unchanged levels in the intervention group. Neuropeptide Y (NPY) increased significantly in the intervention group compared to the reference group. Chromogranin A (CgA) decreased significantly in the intervention group as compared to the reference group. Tumour necrosis factor α (TNFα) decreased significantly in the reference group compared to the intervention group. Logistic regression analysis revealed that group (intervention vs. reference) remained a significant factor in five out of nine predictive models. CONCLUSION: The results indicate that an automatic web-based system might have short-term beneficial physiological and psychological effects and thus might be an opportunity in counteracting some clinically relevant and common stress and health issues of today
Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization
Purpose Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Materials and methods Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. Results No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Conclusion Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images
METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
Purpose: To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research quality of radiomics studies. Methods: We conducted an online modified Delphi study with a group of international experts. It was performed in three consecutive stages: Stage#1, item preparation; Stage#2, panel discussion among EuSoMII Auditing Group members to identify the items to be voted; and Stage#3, four rounds of the modified Delphi exercise by panelists to determine the items eligible for the METRICS and their weights. The consensus threshold was 75%. Based on the median ranks derived from expert panel opinion and their rank-sum based conversion to importance scores, the category and item weights were calculated. Result: In total, 59 panelists from 19 countries participated in selection and ranking of the items and categories. Final METRICS tool included 30 items within 9 categories. According to their weights, the categories were in descending order of importance: study design, imaging data, image processing and feature extraction, metrics and comparison, testing, feature processing, preparation for modeling, segmentation, and open science. A web application and a repository were developed to streamline the calculation of the METRICS score and to collect feedback from the radiomics community. Conclusion: In this work, we developed a scoring tool for assessing the methodological quality of the radiomics research, with a large international panel and a modified Delphi protocol. With its conditional format to cover methodological variations, it provides a well-constructed framework for the key methodological concepts to assess the quality of radiomic research papers. Critical relevance statement: A quality assessment tool, METhodological RadiomICs Score (METRICS), is made available by a large group of international domain experts, with transparent methodology, aiming at evaluating and improving research quality in radiomics and machine learning. Key points: • A methodological scoring tool, METRICS, was developed for assessing the quality of radiomics research, with a large international expert panel and a modified Delphi protocol. • The proposed scoring tool presents expert opinion-based importance weights of categories and items with a transparent methodology for the first time. • METRICS accounts for varying use cases, from handcrafted radiomics to entirely deep learning-based pipelines. • A web application has been developed to help with the calculation of the METRICS score (https://metricsscore.github.io/metrics/METRICS.html) and a repository created to collect feedback from the radiomics community (https://github.com/metricsscore/metrics). Graphical Abstract: [Figure not available: see fulltext.
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