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.

Information Filtering for Ultrasound-based Real-time Registration

This paper presents methods based on Information Filters for solving matching problems with emphasis on real-time, or effectively real-time applications. Both applications discussed in this work deal with ultrasound-based rigid registration in computer-assisted orthopedic surgery. In the first application, the usual workflow of rigid registration is reformulated such that registration algorithms would iterate while the surgeon is acquiring ultrasound images of the anatomy to be operated. Using this effectively real-time approach to registration, the surgeon would then receive feedback in order to better gauge the quality of the final registration outcome. The second application considered in this paper circumvents the need to attach physical markers to bones for anatomical referencing. Experiments using anatomical objects immersed in water are performed in order to evaluate and compare the different methods presented herein, using both 2D as well as real-time 3D ultrasound.

Impaired performance on the rapid visual information processing task (RVIP) could be an endophenotype of schizophrenia

The aim of the present study was to investigate whether healthy first-degree relatives of schizophrenia patients show reduced sensitivity performance, higher intra-individual variability (IIV) in reaction time (RT), and a steeper decline in sensitivity over time in a sustained attention task. Healthy first-degree relatives of schizophrenia patients (n=23) and healthy control subjects (n=46) without a family history of schizophrenia performed a demanding version of the Rapid Visual Information Processing task (RVIP). RTs, hits, false alarms, and the sensitivity index A' were assessed. The relatives were significantly less sensitive, tended to have higher IIV in RT, but sustained the impaired level of sensitivity over time. Impaired performance on the RVIP is a possible endophenotype for schizophrenia. Higher IIV in RT, apparently caused by impaired context representations, might result in fluctuations in control and lead to more frequent attentional lapses.

Geographic information system-based decision support for soil conservation planning in Tajikistan

Soil erosion on sloping agricultural land poses a serious problem for the environment, as well as for production. In areas with highly erodible soils, such as those in loess zones, application of soil and water conservation measures is crucial to sustain agricultural yields and to prevent or reduce land degradation. The present study, carried out in Faizabad, Tajikistan, was designed to evaluate the potential of local conservation measures on cropland using a spatial modelling approach to provide decision-making support for the planning of spatially explicit sustainable land use. A sampling design to support comparative analysis between well-conserved units and other field units was established in order to estimate factors that determine water erosion, according to the Revised Universal Soil Loss Equation (RUSLE). Such factor-based approaches allow ready application using a geographic information system (GIS) and facilitate straightforward scenario modelling in areas with limited data resources. The study showed first that assessment of erosion and conservation in an area with inhomogeneous vegetation cover requires the integration of plot-based cover. Plot-based vegetation cover can be effectively derived from high-resolution satellite imagery, providing a useful basis for plot-wise conservation planning. Furthermore, thorough field assessments showed that 25.7% of current total cropland is covered by conservation measures (terracing, agroforestry and perennial herbaceous fodder). Assessment of the effectiveness of these local measures, combined with the RUSLE calculations, revealed that current average soil loss could be reduced through low-cost measures such as contouring (by 11%), fodder plants (by 16%), and drainage ditches (by 53%). More expensive measures such as terracing and agroforestry can reduce erosion by as much as 63% (for agroforestry) and 93% (for agroforestry combined with terracing). Indeed, scenario runs for different levels of tolerable erosion rates showed that more cost-intensive and technologically advanced measures would lead to greater reduction of soil loss. However, given economic conditions in Tajikistan, it seems advisable to support the spread of low-cost and labourextensive measures.

Cognitive binding in schizophrenia: weakened integration of temporal intersensory information

Cognitive functioning is based on binding processes, by which different features and elements of neurocognition are integrated and coordinated. Binding is an essential ingredient of, for instance, Gestalt perception. We have implemented a paradigm of causality perception based on the work of Albert Michotte, in which 2 identical discs move from opposite sides of a monitor, steadily toward, and then past one another. Their coincidence generates an ambiguous percept of either "streaming" or "bouncing," which the subjects (34 schizophrenia spectrum patients and 34 controls with mean age 27.9 y) were instructed to report. The latter perception is a marker of the binding processes underlying perceived causality (type I binding). In addition to this visual task, acoustic stimuli were presented at different times during the task (150 ms before and after visual coincidence), which can modulate perceived causality. This modulation by intersensory and temporally delayed stimuli is viewed as a different type of binding (type II). We show here, using a mixed-effects hierarchical analysis, that type II binding distinguishes schizophrenia spectrum patients from healthy controls, whereas type I binding does not. Type I binding may even be excessive in some patients, especially those with positive symptoms; Type II binding, however, was generally attenuated in patients. The present findings point to ways in which the disconnection (or Gestalt) hypothesis of schizophrenia can be refined, suggesting more specific markers of neurocognitive functioning and potential targets of treatment.

Insertion of totally implantable venous access devices: an expertise-based, randomized, controlled trial (NCT00600444)

Comparison of two different insertion techniques for implantation of totally implantable access ports (TIAP).

Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks

Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.

Graph-Based Multi-Surface Segmentation of OCT Data Using Trained Hard and Soft Constraints

Optical coherence tomography (OCT) is a well-established image modality in ophthalmology and used daily in the clinic. Automatic evaluation of such datasets requires an accurate segmentation of the retinal cell layers. However, due to the naturally low signal to noise ratio and the resulting bad image quality, this task remains challenging. We propose an automatic graph-based multi-surface segmentation algorithm that internally uses soft constraints to add prior information from a learned model. This improves the accuracy of the segmentation and increase the robustness to noise. Furthermore, we show that the graph size can be greatly reduced by applying a smart segmentation scheme. This allows the segmentation to be computed in seconds instead of minutes, without deteriorating the segmentation accuracy, making it ideal for a clinical setup. An extensive evaluation on 20 OCT datasets of healthy eyes was performed and showed a mean unsigned segmentation error of 3.05 ±0.54 μm over all datasets when compared to the average observer, which is lower than the inter-observer variability. Similar performance was measured for the task of drusen segmentation, demonstrating the usefulness of using soft constraints as a tool to deal with pathologies.