Development of an array of ion-selective microelectrodes aimed for the monitoring of extracellular ionic activities

In this study, we present the development and the characterization of a generic platform for cell culture able to monitor extracellular ionic activities (K+, NH4+) for real-time monitoring of cell-based responses, such as necrosis, apoptosis, or differentiation. The platform for cell culture is equipped with an array of 16 silicon nitride micropipet-based ion-selective microelectrodes with a diameter of either 2 or 6 microm. This array is located at the bottom of a 200-microm-wide and 350-microm-deep microwell where the cells are cultured. The characterization of the ion-selective microelectrode arrays in different standard and physiological solutions is presented. Near-Nernstian slopes were obtained for potassium- (58.6 +/- 0.8 mV/pK, n = 15) and ammonium-selective microelectrodes (59.4 +/- 3.9 mV/pNH4, n = 13). The calibration curves were highly reproducible and showed an average drift of 4.4 +/- 2.3 mV/h (n = 10). Long-term behavior and response after immersion in physiological solutions are also presented. The lifetime of the sensors was found to be extremely long with a high recovery rate.

Mapping material distribution in a heterogeneous sand tank by image analysis

Water flow and solute transport through soils are strongly influenced by the spatial arrangement of soil materials with different hydraulic and chemical properties. Knowing the specific or statistical arrangement of these materials is considered as a key toward improved predictions of solute transport. Our aim was to obtain two-dimensional material maps from photographs of exposed profiles. We developed a segmentation and classification procedure and applied it to the images of a very heterogeneous sand tank, which was used for a series of flow and transport experiments. The segmentation was based on thresholds of soil color, estimated from local median gray values, and of soil texture, estimated from local coefficients of variation of gray values. Important steps were the correction of inhomogeneous illumination and reflection, and the incorporation of prior knowledge in filters used to extract the image features and to smooth the results morphologically. We could check and confirm the success of our mapping by comparing the estimated with the designed sand distribution in the tank. The resulting material map was used later as input to model flow and transport through the sand tank. Similar segmentation procedures may be applied to any high-density raster data, including photographs or spectral scans of field profiles.

Improved Localization of Implanted Subdural Electrode Contacts on MRI Using an Elastic Image Fusion Algorithm in Invasive EEG Recording

BACKGROUND: Accurate projection of implanted subdural electrode contacts in presurgical evaluation of pharmacoresistant epilepsy cases by invasive EEG is highly relevant. Linear fusion of CT and MRI images may display the contacts in the wrong position due to brain shift effects. OBJECTIVE: A retrospective study in five patients with pharmacoresistant epilepsy was performed to evaluate whether an elastic image fusion algorithm can provide a more accurate projection of the electrode contacts on the pre-implantation MRI as compared to linear fusion. METHODS: An automated elastic image fusion algorithm (AEF), a guided elastic image fusion algorithm (GEF), and a standard linear fusion algorithm (LF) were used on preoperative MRI and post-implantation CT scans. Vertical correction of virtual contact positions, total virtual contact shift, corrections of midline shift and brain shifts due to pneumencephalus were measured. RESULTS: Both AEF and GEF worked well with all 5 cases. An average midline shift of 1.7mm (SD 1.25) was corrected to 0.4mm (SD 0.8) after AEF and to 0.0mm (SD 0) after GEF. Median virtual distances between contacts and cortical surface were corrected by a significant amount, from 2.3mm after LF to 0.0mm after AEF and GEF (p<.001). Mean total relative corrections of 3.1 mm (SD 1.85) after AEF and 3.0mm (SD 1.77) after GEF were achieved. The tested version of GEF did not achieve a satisfying virtual correction of pneumencephalus. CONCLUSION: The technique provided a clear improvement in fusion of pre- and post-implantation scans, although the accuracy is difficult to evaluate.

Graphical Model-Based Vertebra Identification from X-Ray Image(s)

Automated identification of vertebrae from X-ray image(s) is an important step for various medical image computing tasks such as 2D/3D rigid and non-rigid registration. In this chapter we present a graphical model-based solution for automated vertebra identification from X-ray image(s). Our solution does not ask for a training process using training data and has the capability to automatically determine the number of vertebrae visible in the image(s). This is achieved by combining a graphical model-based maximum a posterior probability (MAP) estimate with a mean-shift based clustering. Experiments conducted on simulated X-ray images as well as on a low-dose low quality X-ray spinal image of a scoliotic patient verified its performance.

XMapTools: a MATLAB©-based program for electron microprobe X-ray image processing and geothermobarometry

XMapTools is a MATLAB©-based graphical user interface program for electron microprobe X-ray image processing, which can be used to estimate the pressure–temperature conditions of crystallization of minerals in metamorphic rocks. This program (available online at http://www.xmaptools.com) provides a method to standardize raw electron microprobe data and includes functions to calculate the oxide weight percent compositions for various minerals. A set of external functions is provided to calculate structural formulae from the standardized analyses as well as to estimate pressure–temperature conditions of crystallization, using empirical and semi-empirical thermobarometers from the literature. Two graphical user interface modules, Chem2D and Triplot3D, are used to plot mineral compositions into binary and ternary diagrams. As an example, the software is used to study a high-pressure Himalayan eclogite sample from the Stak massif in Pakistan. The high-pressure paragenesis consisting of omphacite and garnet has been retrogressed to a symplectitic assemblage of amphibole, plagioclase and clinopyroxene. Mineral compositions corresponding to ~165,000 analyses yield estimates for the eclogitic pressure–temperature retrograde path from 25 kbar to 9 kbar. Corresponding pressure–temperature maps were plotted and used to interpret the link between the equilibrium conditions of crystallization and the symplectitic microstructures. This example illustrates the usefulness of XMapTools for studying variations of the chemical composition of minerals and for retrieving information on metamorphic conditions on a microscale, towards computation of continuous pressure–temperature-and relative time path in zoned metamorphic minerals not affected by post-crystallization diffusion.

Canopy gaps promote selective stem-cutting by small mammals of two dominant tree species in an African lowland forest: the importance of seedling chemistry

Small mammals can impede tree regeneration by injuring seedlings and saplings in several ways. One fatal way is by severing their stems, but apparently this type of predation is not well-studied in tropical rain forest. Here, we report on the incidence of 'stem-cutting' to new, wild seedlings of two locally dominant, canopy tree species monitored in 40 paired forest understorey and gap-habitat areas in Korup, Cameroon following a 2007 masting event. In gap areas, which are required for the upward growth and sapling recruitment of both species, 137 seedlings of the long-lived, light-demanding, fast-growing large tropical tree (Microberlinia bisulcata) were highly susceptible to stem-cutting (83% of deaths) - it killed 39% of all seedlings over a c. 2-y period. In stark contrast, seedlings of the more shade-tolerant, slower-growing tree species (Tetraberlinia bifoliolata) were hardly attacked (4.3%). In the understorey, however, stem-cutting was virtually absent. Across the gap areas, the incidence of stem-cutting of M. bisulcata seedlings showed significant spatial variation that could not be explained significantly by either canopy openness or Janzen-Connell type effects (proximity and basal area of conspecific adult trees). To examine physical and chemical traits that might explain the species difference to being cut, bark and wood tissues were collected from a separate sample of seedlings in gaps (i.e. not monitored for stem-cutting). These analyses suggested that, compared with T. bifoliolata, the lower stem density, higher Mg and K and fatty acid concentrations in bark, and fewer phenolic and terpene compounds in M. bisulcata seedlings made them more palatable and attractive to small-mammal predators, likely rodents. We conclude that selective stem-cutting is a potent countervailing force to the current local canopy dominance of the grove-forming M. bisulcata by limiting the recruitment and abundance of its saplings. Given the ubiquity of gaps and ground-dwelling rodents in pantropical forests, it would be surprising if this form of lethal browsing was restricted to Korup.

Automatic assessment of time-resolved OCT images for selective retina therapy

Purpose In recent years, selective retina laser treatment (SRT), a sub-threshold therapy method, avoids widespread damage to all retinal layers by targeting only a few. While these methods facilitate faster healing, their lack of visual feedback during treatment represents a considerable shortcoming as induced lesions remain invisible with conventional imaging and make clinical use challenging. To overcome this, we present a new strategy to provide location-specific and contact-free automatic feedback of SRT laser applications. Methods We leverage time-resolved optical coherence tomography (OCT) to provide informative feedback to clinicians on outcomes of location-specific treatment. By coupling an OCT system to SRT treatment laser, we visualize structural changes in the retinal layers as they occur via time-resolved depth images. We then propose a novel strategy for automatic assessment of such time-resolved OCT images. To achieve this, we introduce novel image features for this task that when combined with standard machine learning classifiers yield excellent treatment outcome classification capabilities. Results Our approach was evaluated on both ex vivo porcine eyes and human patients in a clinical setting, yielding performances above 95 % accuracy for predicting patient treatment outcomes. In addition, we show that accurate outcomes for human patients can be estimated even when our method is trained using only ex vivo porcine data. Conclusion The proposed technique presents a much needed strategy toward noninvasive, safe, reliable, and repeatable SRT applications. These results are encouraging for the broader use of new treatment options for neovascularization-based retinal pathologies.

Denoising Your Monte Carlo Renders: Recent Advances in Image Space-Adaptive Sampling and Reconstruction

With the ongoing shift in the computer graphics industry toward Monte Carlo rendering, there is a need for effective, practical noise-reduction techniques that are applicable to a wide range of rendering effects and easily integrated into existing production pipelines. This course surveys recent advances in image-space adaptive sampling and reconstruction algorithms for noise reduction, which have proven very effective at reducing the computational cost of Monte Carlo techniques in practice. These approaches leverage advanced image-filtering techniques with statistical methods for error estimation. They are attractive because they can be integrated easily into conventional Monte Carlo rendering frameworks, they are applicable to most rendering effects, and their computational overhead is modest.