Interactive Volume Rendering with Dynamic Ambient Occlusion and Color Bleeding

We propose a method for rendering volumetric data sets at interactive frame rates while supporting dynamic ambient occlusion as well as an approximation to color bleeding. In contrast to ambient occlusion approaches for polygonal data, techniques for volumetric data sets have to face additional challenges, since by changing rendering parameters, such as the transfer function or the thresholding, the structure of the data set and thus the light interactions may vary drastically. Therefore, during a preprocessing step which is independent of the rendering parameters we capture light interactions for all combinations of structures extractable from a volumetric data set. In order to compute the light interactions between the different structures, we combine this preprocessed information during rendering based on the rendering parameters defined interactively by the user. Thus our method supports interactive exploration of a volumetric data set but still gives the user control over the most important rendering parameters. For instance, if the user alters the transfer function to extract different structures from a volumetric data set the light interactions between the extracted structures are captured in the rendering while still allowing interactive frame rates. Compared to known local illumination models for volume rendering our method does not introduce any substantial rendering overhead and can be integrated easily into existing volume rendering applications. In this paper we will explain our approach, discuss the implications for interactive volume rendering and present the achieved results.     

Voreen: A Rapid-Prototyping Environment for Ray-Casting-Based Volume Visualizations

The Voreen volume-rendering engine provides an environment for realizing volume visualizations, which exploit GPU-based ray casting techniques. To alleviate the development process, visual prototyping can be peformed by editing a data flow network graph. While this environment gives full flexibility when designing novel visualizations, the component-based architecture ensures that the realized visualization techniques can be exploited in interactive applications without any performance penalty.     

Glyph-based SPECT visualization for the diagnosis of coronary artery disease

Myocardial perfusion imaging with single photon emission computed tomography (SPECT) is an established method for the detection and evaluation of coronary artery disease (CAD). State-of-the-art SPECT scanners yield a large number of regional parameters of the left-ventricular myocardium (e.g., blood supply at rest and during stress, wall thickness, and wall thickening during heart contraction) that all need to be assessed by the physician. Today, the individual parameters of this multivariate data set are displayed as stacks of 2D slices, bull's eye plots, or, more recently, surfaces in 3D, which depict the left-ventricular wall. In all these visualizations, the data sets are displayed side-by-side rather than in an integrated manner, such that the multivariate data have to be examined sequentially and need to be fused mentally. This is time consuming and error-prone. In this paper we present an interactive 3D glyph visualization, which enables an effective integrated visualization of the multivariate data. Results from semiotic theory are used to optimize the mapping of different variables to glyph properties. This facilitates an improved perception of important information and thus an accelerated diagnosis. The 3D glyphs are linked to the established 2D views, which permit a more detailed inspection, and to relevant meta-information such as known stenoses of coronary vessels supplying the myocardial region. Our method has demonstrated its potential for clinical routine use in real application scenarios assessed by nuclear physicians.     

CD34+CD33- cells influence days to engraftment and transfusion requirements in autologous blood stem-cell recipients

PURPOSE: To evaluate the reliability of CD34/CD33 subset enumeration as a predictor of hematopoietic repopulating potential in autologous blood stem-cell transplantation and to determine which patient and treatment-related factors affect the timing, quantity, and type of blood stem cells mobilized. PATIENTS AND METHODS: We analyzed blood stem-cell collections from 410 consecutive cancer patients who received mobilization therapy and evaluated factors, including CD34+ subset quantities, that might influence engraftment kinetics and transfusion requirements in autologous blood stem-cell recipients. RESULTS: The majority of patients (97%) mobilized CD34+33- cells, which were usually collected in the greatest quantity on the first day of apheresis. Patients who received only growth factor mobilized the highest percentage of CD34+33- cells. Extensive prior chemotherapy limited the collection of CD34+33- cells. In addition to patient diagnosis (P < .006) and total CD34+ cell dose (P = .0001), CD34+33- cell dose (P < .005) and percentage of CD34+33- cells (P < .005) were identified as independent factors significantly predictive of engraftment kinetics. CD34+33- cell dose (R2 < or = .177; P < .0001) was a strong and the only significant predictor of RBC and platelet transfusion requirements. Furthermore, independent of the total CD34+ cell dose, as the CD34+33- cell dose increased, days to neutrophil recovery, days to platelet recovery, and transfusion requirements decreased. CONCLUSION: These findings show that CD34+33- cells are readily collected in most cancer patients and significantly influence engraftment kinetics and transfusion requirements in autologous blood stem-cell recipients. CD34+33- cell quantity of the blood stem-cell graft appears to be a more reliable predictor of hematopoietic recovery rates than total CD34+ cell quantity in this setting.