Hybrid Rugosity Mesostructures (HRMs) for fast and accurate rendering of fine haptic detail

The haptic rendering of surface mesostructure (fine relief features) in dense triangle meshes requires special structures, equipment, and high sampling rates for detailed perception of rugged models. Low cost approaches render haptic texture at the expense of fidelity of perception. We propose a faster method for surface haptic rendering using image-based Hybrid Rugosity Mesostructures (HRMs), paired maps with per-face heightfield displacements and normal maps, which are layered on top of a much decimated mesh, effectively adding greater surface detail than actually present in the geometry. The haptic probe’s force response algorithm is modulated using the blended HRM coat to render dense surface features at much lower costs. The proposed method solves typical problems at edge crossings, concave foldings and texture transitions. To prove the wellness of the approach, a usability testbed framework was built to measure and compare experimental results of haptic rendering approaches in a common set of specially devised meshes, HRMs, and performance tests. Trial results of user testing evaluations show the goodness of the proposed HRM technique, rendering accurate 3D surface detail at high sampling rates, deriving useful modeling and perception thresholds for this technique.Peer ReviewedPostprint (published version

Stochastic Volume Rendering of Multi-Phase SPH Data

In this paper, we present a novel method for the direct volume rendering of large smoothed‐particle hydrodynamics (SPH) simulation data without transforming the unstructured data to an intermediate representation. By directly visualizing the unstructured particle data, we avoid long preprocessing times and large storage requirements. This enables the visualization of large, time‐dependent, and multivariate data both as a post‐process and in situ. To address the computational complexity, we introduce stochastic volume rendering that considers only a subset of particles at each step during ray marching. The sample probabilities for selecting this subset at each step are thereby determined both in a view‐dependent manner and based on the spatial complexity of the data. Our stochastic volume rendering enables us to scale continuously from a fast, interactive preview to a more accurate volume rendering at higher cost. Lastly, we discuss the visualization of free‐surface and multi‐phase flows by including a multi‐material model with volumetric and surface shading into the stochastic volume rendering

Misleading Presentations of Malignant Breast Diseases – Role of Clinical Cytology

We described two examples with misleading presentations to draw attention to the role of clinical cytology as a part of multidisciplinary approach to breast lesions. In the first case – Paget’s disease of the nipple, there was no obvious clinical and radiological evidence of breast cancer, while the second case – primary non-Hodgkin lymphoma of the breast imitated advanced breast carcinoma. The question is whether accurate and fast diagnoses can be made without cytological examinations. It must be kept in mind that first-hand clinical information and contact with the patient is necessary in rendering accurate cytological diagnoses

Using high resolution displays for high resolution cardiac data

The ability to perform fast, accurate, high resolution visualization is fundamental to improving our understanding of anatomical data. As the volumes of data increase from improvements in scanning technology, the methods applied to rendering and visualization must evolve. In this paper we address the interactive display of data from high resolution MRI scanning of a rabbit heart and subsequent histological imaging. We describe a visualization environment involving a tiled LCD panel display wall and associated software which provide an interactive and intuitive user interface. The oView software is an OpenGL application which is written for the VRJuggler environment. This environment abstracts displays and devices away from the application itself, aiding portability between different systems, from desktop PCs to multi-tiled display walls. Portability between display walls has been demonstrated through its use on walls at both Leeds and Oxford Universities. We discuss important factors to be considered for interactive 2D display of large 3D datasets, including the use of intuitive input devices and level of detail aspects

Misleading Presentations of Malignant Breast Diseases – Role of Clinical Cytology

We described two examples with misleading presentations to draw attention to the role of clinical cytology as a part of multidisciplinary approach to breast lesions. In the first case – Paget’s disease of the nipple, there was no obvious clinical and radiological evidence of breast cancer, while the second case – primary non-Hodgkin lymphoma of the breast imitated advanced breast carcinoma. The question is whether accurate and fast diagnoses can be made without cytological examinations. It must be kept in mind that first-hand clinical information and contact with the patient is necessary in rendering accurate cytological diagnoses

Probabilistic segmentation of volume data for visualization using SOM-PNN classifier

We present a new probabilistic classifier, called SOM-PNN classifier, for volume data classification and visualization. The new classifier produces probabilistic classification with Bayesian confidence measure which is highly desirable in volume rendering. Based on the SOM map trained with a large training data set, our SOM-PNN classifier performs the probabilistic classification using the PNN algorithm. This combined use of SOM and PNN overcomes the shortcomings of the parametric methods, the nonparametric methods, and the SOM method. The proposed SOM-PNN classifier has been used to segment the CT sloth data and the 20 human MRI brain volumes resulting in much more informative 3D rendering with more details and less artifacts than other methods. Numerical comparisons demonstrate that the SOM-PNN classifier is a fast, accurate and probabilistic classifier for volume rendering.published_or_final_versio

Precision spectroscopy by photon-recoil signal amplification

Precision spectroscopy of atomic and molecular ions offers a window to new physics, but is typically limited to species with a cycling transition for laser cooling and detection. Quantum logic spectroscopy has overcome this limitation for species with long-lived excited states. Here, we extend quantum logic spectroscopy to fast, dipole-allowed transitions and apply it to perform an absolute frequency measurement. We detect the absorption of photons by the spectroscopically investigated ion through the photon recoil imparted on a co-trapped ion of a different species, on which we can perform efficient quantum logic detection techniques. This amplifies the recoil signal from a few absorbed photons to thousands of fluorescence photons. We resolve the line center of a dipole-allowed transition in 40Ca+ to 1/300 of its observed linewidth, rendering this measurement one of the most accurate of a broad transition. The simplicity and versatility of this approach enables spectroscopy of many previously inaccessible species.Comment: 25 pages, 6 figures, 1 table, updated supplementary information, fixed typo