80 research outputs found
Variable mixture ratio performance through nitrogen augmentation
High/variable mixture ratio O2/H2 candidate engine cycles are examined for earth-to-orbit vehicle application. Engine performance and power balance information are presented for the candidate cycles relative to chamber pressure, bulk density, and mixture ratio. Included in the cycle screening are concepts where a third fluid (liquid nitrogen) is used to achieve a variable mixture ratio over the trajectory from liftoff to earth orbit. The third fluid cycles offer a very low risk, fully reusable, low operation cost alternative to high/variable mixture ratio bipropellant cycles. Variable mixture ratio engines with extendible nozzle are slightly lower performing than a single mixture ratio engine (MR = 7:1) with extendible nozzle. Dual expander engines (MR = 7:1) have slightly better performance than the single mixture ratio engine. Dual fuel dual expander engines offer a 16 percent improvement over the single mixture ratio engine
Lung Segmentation in 4D CT Volumes Based on Robust Active Shape Model Matching
Dynamic and longitudinal lung CT imaging produce 4D lung image data sets, enabling applications like radiation treatment planning or assessment of response to treatment of lung diseases. In this paper, we present a 4D lung segmentation method that mutually utilizes all individual CT volumes to derive segmentations for each CT data set. Our approach is based on a 3D robust active shape model and extends it to fully utilize 4D lung image data sets. This yields an initial segmentation for the 4D volume, which is then refined by using a 4D optimal surface finding algorithm. The approach was evaluated on a diverse set of 152 CT scans of normal and diseased lungs, consisting of total lung capacity and functional residual capacity scan pairs. In addition, a comparison to a 3D segmentation method and a registration based 4D lung segmentation approach was performed. The proposed 4D method obtained an average Dice coefficient of 0.9773±0.0254, which was statistically significantly better (p value âȘ0.001) than the 3D method (0.9659±0.0517). Compared to the registration based 4D method, our method obtained better or similar performance, but was 58.6% faster. Also, the method can be easily expanded to process 4D CT data sets consisting of several volumes
Robust Initialization of Active Shape Models for Lung Segmentation in CT Scans: A Feature-Based Atlas Approach
Model-based segmentation methods have the advantage of incorporating a priori shape information into the segmentation process but suffer from the drawback that the model must be initialized sufficiently close to the target. We propose a novel approach for initializing an active shape model (ASM) and apply it to 3D lung segmentation in CT scans. Our method constructs an atlas consisting of a set of representative lung features and an average lung shape. The ASM pose parameters are found by transforming the average lung shape based on an affine transform computed from matching features between the new image and representative lung features. Our evaluation on a diverse set of 190 images showed an average dice coefficient of 0.746 ± 0.068 for initialization and 0.974 ± 0.017 for subsequent segmentation, based on an independent reference standard. The mean absolute surface distance error was 0.948 ± 1.537 mm. The initialization as well as segmentation results showed a statistically significant improvement compared to four other approaches. The proposed initialization method can be generalized to other applications employing ASM-based segmentation
An Artificial SEI Layer Based on an Inorganic Coordination Polymer with Self-Healing Ability for Long-Lived Rechargeable Lithium-Metal Batteries
Upon immersion of a lithium (Li) anode into a diluted 0.05 to 0.20â
M dimethoxyethane solution of the phosphoric-acid derivative (CFCHO)P(O)OH (HBFEP), an artificial solid-electrolyte interphase (SEI) is generated on the Li-metal surface. Hence, HBFEP reacts on the surface to the corresponding Li salt (LiBFEP), which is a Li-ion conducting inorganic coordination polymer. This film exhibits â due to the reversibly breaking ionic bonds â self-healing ability upon cycling-induced volume expansion of Li. The presence of LiBFEP as the major component in the artificial SEI is proven by ATR-IR and XPS measurements. SEM characterization of HBFEP-treated Li samples reveals porous layers on top of the Li surface with at least 3â
ÎŒm thickness. LiâLi symmetrical cells with HBFEP-modified Li electrodes show a three- to almost fourfold cycle-lifetime increase at 0.1â
mAâcm in a demanding model electrolyte that facilitates fast battery failure (1â
M LiOTf in TEGDME). Hence, the LiBFEP-enriched layer apparently acts as a Li-ion conducting protection barrier between Li and the electrolyte, enhancing the rechargeability of Li electrodes
Comparative Study With New Accuracy Metrics for Target Volume Contouring in PET Image Guided Radiation Therapy
[EN] The impact of positron emission tomography (PET)
on radiation therapy is held back by poor methods of defining functional
volumes of interest. Many new software tools are being proposed
for contouring target volumes but the different approaches
are not adequately compared and their accuracy is poorly evaluated
due to the ill-definition of ground truth. This paper compares
the largest cohort to date of established, emerging and proposed
PET contouring methods, in terms of accuracy and variability.
We emphasize spatial accuracy and present a new metric
that addresses the lack of unique ground truth. Thirty methods
are used at 13 different institutions to contour functional volumes
of interest in clinical PET/CT and a custom-built PET phantom representing typical problems in image guided radiotherapy. Contouring
methods are grouped according to algorithmic type, level
of interactivity and how they exploit structural information in hybrid
images. Experiments reveal benefits of high levels of user interaction,
as well as simultaneous visualization of CT images and
PET gradients to guide interactive procedures. Method-wise evaluation
identifies the danger of over-automation and the value of
prior knowledge built into an algorithm.For retrospective patient data and manual ground truth delineation, the authors wish to thank S. Suilamo, K. Lehtio, M. Mokka, and H. Minn at the Department of Oncology and Radiotherapy, Turku University Hospital, Finland. This study was funded by the Finnish Cancer Organisations.Shepherd, T.; TerÀs, M.; Beichel, RR.; Boellaard, R.; Bruynooghe, M.; Dicken, V.; Gooding, MJ.... (2012). Comparative Study With New Accuracy Metrics for Target Volume Contouring in PET Image Guided Radiation Therapy. IEEE Transactions on Medical Imaging. 31(12):2006-2024. doi:10.1109/TMI.2012.2202322S20062024311
Semi-Automatic Anatomical Tree Matching for Landmark-Based Elastic Registration of Liver Volumes
Detection of selected pathogens in ticks collected from cats and dogs in the WrocĆaw Agglomeration, South-West Poland
Automated 3-D Segmentation of Lungs With Lung Cancer in CT Data Using a Novel Robust Active Shape Model Approach
Graph-Based Airway Tree Reconstruction From Chest CT Scans: Evaluation of Different Features on Five Cohorts
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