Multi-modal diffeomorphic demons registration based on point-wise mutual information

In this paper we propose a variational approach for multimodal image registration based on the diffeomorphic demons algorithm. Diffeomorphic demons has proven to be a robust and efficient way for intensity-based image registration. However, the main drawback is that it cannot deal with multiple modalities. We propose to replace the standard demons similarity metric (image intensity differences) by point-wise mutual information (PMI) in the energy function. By comparing the accuracy between our PMI based diffeomorphic demons and the B-Spline based free-form deformation approach (FFD) on simulated deformations, we show the proposed algorithm performs significantly better.

Rapid exclusion or confirmation of heparin-induced thrombocytopenia: a single-center experience with 1,291 patients

The current gold-standard for diagnosing heparin-induced thrombocytopenia is the detection of platelet-activating antibodies by means of functional assays which, since they are time consuming and not widely available, are not suited to guiding acute treatment decisions. The objective of our study was to assess the ability of more rapid immunoassays to predict the presence of functionally relevant anti-platelet factor 4/heparin-antibodies.

Short-Term Effects of Social Exclusion at work and Worries on Sleep

The present study investigated short-term effects of daily social exclusion at work on various indicators of sleep quality and tested the mediating role of work-related worries using a time-based diary study with ambulatory assessments of sleep quality. Ninety full-time employees participated in a 2-week data collection. Multilevel analyses revealed that daily workplace social exclusion and work-related worries were positively related to sleep fragmentation in the following night. Daily social exclusion, however, was unrelated to sleep onset latency, sleep efficiency and self-reported sleep quality. Moreover, worries did not mediate the effect of social exclusion at work on sleep fragmentation. Theoretical and practical implications of the results are discussed.

"It was hard to come to mutual understanding..." - Multidimensionality of social learning processes in natural resource use in India, Africa and Latin America

Sustainable natural resource use requires that multiple actors reassess their situation in a systemic perspective. This can be conceptualised as a social learning process between actors from rural communities and the experts from outside organisations. A specifically designed workshop oriented towards a systemic view of natural resource use and the enhancement of mutual learning between local and external actors, provided the background for evaluating the potentials and constraints of intensified social learning processes. Case studies in rural communities in India, Bolivia, Peru and Mali showed that changes in the narratives of the participants of the workshop followed a similar temporal sequence relatively independently from their specific contexts. Social learning processes were found to be more likely to be successful if they 1) opened new space for communicative action, allowing for an intersubjective re-definition of the present situation, 2) contributed to rebalance the relationships between social capital and social, emotional and cognitive competencies within and between local and external actors.

Unifying energy minimization and mutual information maximization for robust 2D/3D registration of X-ray and CT images

Similarity measure is one of the main factors that affect the accuracy of intensity-based 2D/3D registration of X-ray fluoroscopy to CT images. Information theory has been used to derive similarity measure for image registration leading to the introduction of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. Previous attempt to incorporate spatial information into mutual information either requires computing the entropy of higher dimensional probability distributions, or is not robust to outliers. In this paper, we show how to incorporate spatial information into mutual information without suffering from these problems. Using a variational approximation derived from the Kullback-Leibler bound, spatial information can be effectively incorporated into mutual information via energy minimization. The resulting similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on datasets of two applications: (a) intra-operative patient pose estimation from a few (e.g. 2) calibrated fluoroscopic images, and (b) post-operative cup alignment estimation from single X-ray radiograph with gonadal shielding.

Species-level selection reduces selfishness through competitive exclusion

Adaptation does not necessarily lead to traits which are optimal for the population. This is because selection is often the strongest at the individual or gene level. The evolution of selfishness can lead to a 'tragedy of the commons', where traits such as aggression or social cheating reduce population size and may lead to extinction. This suggests that species-level selection will result whenever species differ in the incentive to be selfish. We explore this idea in a simple model that combines individual-level selection with ecology in two interacting species. Our model is not influenced by kin or trait-group selection. We find that individual selection in combination with competitive exclusion greatly increases the likelihood that selfish species go extinct. A simple example of this would be a vertebrate species that invests heavily into squabbles over breeding sites, which is then excluded by a species that invests more into direct reproduction. A multispecies simulation shows that these extinctions result in communities containing species that are much less selfish. Our results suggest that species-level selection and community dynamics play an important role in regulating the intensity of conflicts in natural populations.