RÉSUMÉ
Carotid atherosclerosis is one of the leading causes of cardiovascular disease with high mortality. Multi-contrast MRI can identify atherosclerotic plaque components with high sensitivity and specificity. Accurate segmentation of the diseased carotid artery from MR images is very essential to quantitatively evaluate the state of atherosclerosis. However, due to the complex morphology of atherosclerosis plaques and the lack of well-annotated data, the segmentation of lumen and wall is very challenging. Different from popular deep learning methods, in this paper, we propose an integration segmentation framework by introducing a lightweight prediction model and improved optimal surface graph cuts (OSG), which adopts a simplified flow line sampling and post-reconstructing method to reduce the cost of graph construction. Moreover, a flexibly adaptive smoothing penalty is presented for maintaining the shape of diseased carotid surface. For the experiments, we have collected an MR image dataset from patients with carotid atherosclerosis and evaluated our method by cross-validation. It can reach 89.68%/80.29% of dice coefficients and 0.2480 mm/0.3396 mm of average surface distances on the lumen/wall segmentation, respectively. The experimental results show that our method can generate precise and reliable segmentation of both lumen and wall of diseased carotid artery with a quite small training cost.
Sujet(s)
Athérosclérose , Artériopathies carotidiennes , Plaque d'athérosclérose , Artères carotides/imagerie diagnostique , Artériopathies carotidiennes/imagerie diagnostique , Artère carotide commune , Humains , Traitement d'image par ordinateur/méthodes , Imagerie par résonance magnétique , Plaque d'athérosclérose/imagerie diagnostiqueRÉSUMÉ
The influence of CO2, H2O and SO2 on the NO reduction by CO over Fe/Co activated semi-coke catalyst was investigated in a simulated rotary reactor. The results showed that, in the simulated rotary reactor, the influence of CO2 and H2O on the NO adsorption was significant at low temperatures, and the inhibition became weak when increasing the temperature. However, the NO adsorption efficiency could not be improved by increasing temperature after catalyst sulfur poisoning. The heavily inhibited NO adsorption process, which was due to the competitive adsorption and formation of the sulfate, resulted in a low NO reduction efficiency in the presence of CO2, H2O or SO2. The in situ DRIFT study showed that the dominant effect of CO2, H2O and SO2 on the NO adsorption was the inhibition of the free nitrate ions formation. In addition, the introduction of CO2, H2O and SO2 could not change the route of NO reduction, but just reduced the degree of the NO + CO reduction.