Solution of Inverse Problem with the One Primary and One Secondary Particle Model (OPOSPM) Coupled with Computational Fluid Dynamics (CFD)

AbstractThe reduced one group population balance (PBE) model, the One Primary and One Secondary Particle Model (OPOSPM) is developed for a liquid extraction column. It is used because of its simplicity and the ability to reproducemost of the information contained in the PBE. It is usedto estimate the optimum droplet breakage and coalescence parameters using steady state experimental data. The data is obtained from a pilot plant liquid extraction column of 80mm diameter and 4.4 m height for toluene-acetone-water chemical test system as recommended by the European Federation of Chemical Engineering (EFCE). In this contribution Coulaloglou and Tavlarides (1977)breakage and coalescence model is studied to obtain the parameters by solving a population balance inverse problem. The estimated droplet parameters are used as input parameters for the CFD simulation and in the simulation program PPBLAB.The optimized values were found to predict accurately the mean dispersed phase holdup, mean droplet diameter and the concentration profile for the continuous and dispersed phase along the extraction column height

An open environment CT-US fusion for tissue segmentation during interventional guidance.

Therapeutic ultrasound (US) can be noninvasively focused to activate drugs, ablate tumors and deliver drugs beyond the blood brain barrier. However, well-controlled guidance of US therapy requires fusion with a navigational modality, such as magnetic resonance imaging (MRI) or X-ray computed tomography (CT). Here, we developed and validated tissue characterization using a fusion between US and CT. The performance of the CT/US fusion was quantified by the calibration error, target registration error and fiducial registration error. Met-1 tumors in the fat pads of 12 female FVB mice provided a model of developing breast cancer with which to evaluate CT-based tissue segmentation. Hounsfield units (HU) within the tumor and surrounding fat pad were quantified, validated with histology and segmented for parametric analysis (fat: -300 to 0 HU, protein-rich: 1 to 300 HU, and bone: HU>300). Our open source CT/US fusion system differentiated soft tissue, bone and fat with a spatial accuracy of ∼1 mm. Region of interest (ROI) analysis of the tumor and surrounding fat pad using a 1 mm(2) ROI resulted in mean HU of 68±44 within the tumor and -97±52 within the fat pad adjacent to the tumor (p<0.005). The tumor area measured by CT and histology was correlated (r(2) = 0.92), while the area designated as fat decreased with increasing tumor size (r(2) = 0.51). Analysis of CT and histology images of the tumor and surrounding fat pad revealed an average percentage of fat of 65.3% vs. 75.2%, 36.5% vs. 48.4%, and 31.6% vs. 38.5% for tumors <75 mm(3), 75-150 mm(3) and >150 mm(3), respectively. Further, CT mapped bone-soft tissue interfaces near the acoustic beam during real-time imaging. Combined CT/US is a feasible method for guiding interventions by tracking the acoustic focus within a pre-acquired CT image volume and characterizing tissues proximal to and surrounding the acoustic focus

linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser

In biology, we are often confronted with information-rich, large-scale trajectory data, but exploring and communicating patterns in such data can be a cumbersome task. Ideally, the data should be wrapped with an interactive visualisation in one concise packet that makes it straightforward to create and test hypotheses collaboratively. To address these challenges, we have developed a tool, linus, which makes the process of exploring and sharing 3D trajectories as easy as browsing a website. We provide a python script that reads trajectory data, enriches them with additional features such as edge bundling or custom axes, and generates an interactive web-based visualisation that can be shared online. linus facilitates the collaborative discovery of patterns in complex trajectory data

Exploration and comparison of trajectory data

Full rendering of a high number of trajectories (e.g. streamline tractograms of DTI images, or traffic routes) leads to heavy occlusion and superimposition, which reduces the perception of the main characteristics of the data. Evaluation and exploration can therefore be a challenge for the user. These difficulties of understanding are exacerbated when two datasets, like data from different time points, should be compared. We present a method to facilitate the navigation through trajectory sets and enable comparison of two datasets in one image. We minimize occlusion by bundling the trajectories, resulting in a skeleton-like representation, and allow the user to interactively explore regions of interest in detail

Eurographics Conference on Visualization (EuroVis) (2013), pp. 1–4

Combined volume registration and visualization online submission 108 We present a method for combining and visualizing a set of overlapping volume images with high resolution but limited spatial extent. Our system combines the calculation of a registration metric with ray casting for direct volume rendering into a combined operation performed on the graphics processing unit (GPU). The combined calculation reduces memory traffic, increases rendering frame rate, and makes possible interactive-speed, usersupervised, semi-automatic combination of many component volume images. For volumes which do not overlap any other imaged volume, the system uses contextual information provided in the form of an overall 2D background image to calculate a registration metric

Determining and Visualizing Potential Sources of Floods

In this paper, we visually analyze spatio-temporal patterns of different hydrologic parameters relevant for flooding. On the basis of data from climate simulations with a high resolution regional atmosphere model, several extreme events are selected for different river catchments in Germany. By visually comparing the spatial distribution of the main contributions to the run-off along with their temporal evolution for a time period in the 20th and the 21th century, impacts of climate change on the hydrological cycle can be identified