Yaoping Hu

The use of microscopy and three-dimensional visualization to evaluate the structure of microbial biofilms cultivated in the Calgary Biofilm Device

Microbes frequently live within multicellular, solid surface-attached assemblages termed biofilms. These microbial communities have architectural features that contribute to population heterogeneity and consequently to emergent cell functions. Therefore, three-dimensional (3D) features of biofilm structure are important for understanding the physiology and ecology of these microbial systems. This paper details several protocols for scanning electron microscopy and confocal laser scanning microscopy (CLSM) of biofilms grown on polystyrene pegs in the Calgary Biofilm Device (CBD). Furthermore, a procedure is described for image processing of CLSM data stacks using amira™, a virtual reality tool, to create surface and/or volume rendered 3D visualizations of biofilm microorganisms. The combination of microscopy with microbial cultivation in the CBD — an apparatus that was designed for highthroughput susceptibility testing — allows for structure-function analysis of biofilms under multivariate growth and exposure conditions.

Metal Ions May Suppress or Enhance Cellular Differentiation in Candida albicans and Candida tropicalis Biofilms

ABSTRACT Candida albicans and Candida tropicalis are polymorphic fungi that develop antimicrobial-resistant biofilm communities that are characterized by multiple cell morphotypes. This study investigated cell type interconversion and drug and metal resistance as well as community organization in biofilms of these microorganisms that were exposed to metal ions. To study this, Candida biofilms were grown either in microtiter plates containing gradient arrays of metal ions or in the Calgary Biofilm Device for high-throughput susceptibility testing. Biofilm formation and antifungal resistance were evaluated by viable cell counts, tetrazolium salt reduction, light microscopy, and confocal laser scanning microscopy in conjunction with three-dimensional visualization. We discovered that subinhibitory concentrations of certain metal ions (CrO42−, Co2+, Cu2+, Ag+, Zn2+, Cd2+, Hg2+, Pb2+, AsO2−, and SeO32−) caused changes in biofilm structure by blocking or eliciting the transition between yeast and hyphal cell types. Four distinct biofilm community structure types were discerned from these data, which were designated “domed,” “layer cake,” “flat,” and “mycelial.” This study suggests that Candida biofilm populations may respond to metal ions to form cell-cell and solid-surface-attached assemblages with distinct patterns of cellular differentiation.

Effects of the Alignment Between a Haptic Device and Visual Display on the Perception of Object Softness

Virtual reality (VR) has been gaining popularity in surgical planning and simulation. Most VR surgical simulation systems provide haptic (pertinent to the sense of touch) and visual information simultaneously using certain alignments between a haptic device and visual display. A critical aspect of such VR surgical systems is to represent both haptic and visual information accurately to avoid perceptual illusions (e.g., to distinguish the softness of organs/tissues). This study compared three different alignments (same-location alignment, vertical alignment, and horizontal alignment) between a haptic device and visual display that are widely used in VR systems. We conducted three experiments to study the influence of each alignment on the perception of object softness. In each experiment, we tested 15 different human subjects with varying availability of haptic and visual information. During each trial, the task of the subject was to discriminate object softness between two deformable balls in different viewing angles. We analyzed the following dependent measurements: subject perception of object softness and objective measurements of maximum force and maximum pressing depth. The analysis results reveal that all three alignments (independent variables) have similar effect on subjective perception of object softness within the interval of viewing angles from -7.5° to +7.5°. The viewing angle does not affect objective measurements. The same-location alignment requires less physical effort compared with the other two alignments. These observations have implications in creating accurate simulation and interaction for VR surgical systems.

Haptic and gesture-based interactions for manipulating geological datasets

In this paper, we report the first step of our ongoing research toward the creation of an intuitive and interactive environment for manipulating and analyzing geological datasets. This first step of our project aimed at the development of a manipulation system through the employment of haptic sense and gesture detection, into a virtual environment. The developed prototype integrates stereoscopic interactive visual rendering, haptic feedback and real-time hand tracking via a range camera, in a multithreaded architecture. Our prototype has been tested with both a synthetic 3D terrain and geological datasets. Our first results confirm the effectiveness of the selected architecture.

The role of viewing angle in integrating the senses of vision and touch for perception of object softness

Enabling surgeons to interact intuitively and accurately with virtual reality (VR)¿based environments using their senses of vision and touch (e.g., to distinguish the softness of tissues) is a challenging issue for surgical planning. This paper presents the results of two experiments that were conducted to determine how viewing angle affects the perception of object softness and to investigate the mechanisms for integrating the senses of vision and touch. The two experiments used virtual reality setups with different locations of a haptic device. In each experiment, 15 human subjects were tested in cases where both visual and touch (haptic) information was available and again when only visual or haptic information was available. In each trial, subjects were asked to select the harder object among two deformable balls placed at different viewing angles. The results of both experiments showed that viewing angle affects the perception of object softness: the larger the viewing angle, the harder the ball was perceived to be. When two viewing angles differed by at least 15°, there was a significant difference in perceived object softness. By computing the individual and combined weights of visual and haptic information, it was determined that visual information and haptic information depend upon each other, contradicting the assumption of independence employed in other studies. Comparison of the two experiments revealed that the location of the haptic device also affects the perception of object softness.

The effect of incongruent delay on guided haptic training

Virtual Reality (VR) technology has great potential as a tool for training. Remote haptic virtual environments (VE) allow multiple users to interact in the same virtual space to accomplish tasks. Combining these ideas, it is possible to apply a remote VE to connect skilled trainers with remote trainees for training. In this paper we examined guided haptic training as an interaction method where one user guides another user through a VR simulation. We considered interaction with virtual soft objects, which were pressed and deformed. Within a remote VE for guided haptic training, network factors such as delay could influence how the guided user perceives object softness. In this paper, we examined how incongruent delays between the streams of visual and haptic information affect this perception. We found that when haptic information was delayed 133.33 ms beyond visual information there was a statistically significant difference in the perception of object softness. These preliminary observations can be used to locate a threshold for applying to future remote guided VE training tools.

An evaluation method for real-time soft-tissue model used for multi-vertex palpation

Soft tissue palpation plays an important role in diagnosing various diseases. Palpating skills are tedious to learn due to the difficulty of describing the sense of touch. Because of its interactive nature, a virtual reality (VR) training system embedding with real-time soft-tissue models may be helpful to teach such skills to medical residents. Studies show that such a VR system impacts human perception during palpating at various levels, largely due to the real-time models. Therefore, we propose a formal method for evaluating real-time models considering the human perception. Based upon surface (multi-vertex) contact with 4 force distributions, the evaluation compared a real-time model with a Finite Element Method (FEM) model featuring physical parameters. The comparison consisted of two statistical approaches - ANOVA and Bland and Altman agreement- to assess both visual displacement and force feedback. A case study demonstrated the advantages provided by this evaluation method.

A viscoelastic model of a breast phantom for real-time palpation

Palpation of soft tissues helps to diagnose varying diseases within the tissues. Using a phantom, the current method of training palpation lacks for feedback of the training. Similar to a robot-assisted surgical system, a virtual reality (VR) system could be potential for such training due to its interactive nature. In such a VR system, studies revealed the observation that the human perception of objects is insensitive to subtle discrepancies in a simulation. Based upon this observation, we propose a real-time viscoelastic model of a breast phantom (as soft tissues). The model consists of a surface membrane and an inside gel. We evaluate this model through a comparison with a Finite Element Method (FEM) model, featuring physical parameters and different force contacts. The results show that the model can handle multi vertex force contact on an arbitrary location and yields reasonable accurate deformation compared to the FEM model.

Biofilm structure differentiation based on multi-resolution analysis.

Quantitative parameters for describing the morphology of biofilms are crucial towards establishing the influence of growing conditions on biofilm structure. Parameters used in earlier studies generally fail to differentiate complex three-dimensional structures. This article presents a novel approach of defining a parameter vector based on the energy signature of multi-resolution analysis, which was applied to differentiating biofilm structures from confocal laser scanning microscopy (CLSM) biofilm images. The parameter vector distinguished differences in the spatial arrangements of synthetic images. For real CLSM images, this parameter vector detected subtle differences in biofilm structure for three sample cases: (1) two adjacent images of a CLSM stack; (2) two partial stacks from the same CLSM stack with equal numbers of images but spatially offset by one image; and (3) three complete CLSM stacks from different bacterial strains. It was also observed that filtering the noise in CLSM images enhanced the sensitivity of the differentiation using our parameter vector.

Towards an analytic haptic model for force rendering of soft-tissue dissection

Both surgical simulation and robot-assisted surgery require haptic models of tool-tissue interaction for force rendering. Most efforts of haptic modeling have focused on characterizing tool-tissue interaction of soft-tissue indentation, insertion and cutting. Less attention has been devoted to soft-tissue dissection however. For the dissection, haptic models remain elusive to meet two requirements as: to represent nonlinearity of soft-tissue responses and to comply with the time constraint of 1 ms for force rendering. Hence, this paper presents a modeling framework towards developing an analytic haptic model for force rendering of the dissection. Based on estimation theories, the framework devises an analytic model to approximate an empirical force-distance profile of the dissection. Applying the framework to 2 different empirical profiles as use cases, the derived models estimated about 72% and 91% of the empirical data, respectively. Algorithm implementation of these models in Matlab yielded a computational time of about 24 µs, much less than 1 ms. The outcomes indicate a potential of using the framework to develop an analytic haptic model for force rendering of soft-tissue dissection.