26,100 research outputs found
Adversarial Convolutional Networks with Weak Domain-Transfer for Multi-sequence Cardiac MR Images Segmentation
Analysis and modeling of the ventricles and myocardium are important in the
diagnostic and treatment of heart diseases. Manual delineation of those tissues
in cardiac MR (CMR) scans is laborious and time-consuming. The ambiguity of the
boundaries makes the segmentation task rather challenging. Furthermore, the
annotations on some modalities such as Late Gadolinium Enhancement (LGE) MRI,
are often not available. We propose an end-to-end segmentation framework based
on convolutional neural network (CNN) and adversarial learning. A dilated
residual U-shape network is used as a segmentor to generate the prediction
mask; meanwhile, a CNN is utilized as a discriminator model to judge the
segmentation quality. To leverage the available annotations across modalities
per patient, a new loss function named weak domain-transfer loss is introduced
to the pipeline. The proposed model is evaluated on the public dataset released
by the challenge organizer in MICCAI 2019, which consists of 45 sets of
multi-sequence CMR images. We demonstrate that the proposed adversarial
pipeline outperforms baseline deep-learning methods.Comment: 9 pages, 4 figures, conferenc
Effect of depreciation of the public goods in spatial public goods games
In this work, depreciated effect of the public goods is considered in the
public goods games, which is realized by rescaling the multiplication factor r
of each group as r' = r(nc/G)^beta (beat>= 0). It is assumed that each
individual enjoys the full profit of the public goods if all the players of
this group are cooperators, otherwise, the value of the public goods is reduced
to r'. It is found that compared with the original version (beta = 0),
emergence of cooperation is remarkably promoted for beta > 0, and there exit
optimal values of beta inducing the best cooperation. Moreover, the optimal
plat of beta broadens as r increases. Furthermore, effect of noise on the
evolution of cooperation is studied, it is presented that variation of
cooperator density with the noise is dependent of the value of beta and r, and
cooperation dominates over most of the range of noise at an intermediate value
of beta = 1.0. We study the initial distribution of the multiplication factor
at beta = 1.0, and find that all the distributions can be described as Gauss
distribution
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