An Interactive Game with Virtual Reality Immersion to Improve Cultural Sensitivity in Health Care.

Purpose: Biased perceptions of individuals who are not part of one's in-groups tend to be negative and habitual. Because health care professionals are no less susceptible to biases than are others, the adverse impact of biases on marginalized populations in health care warrants continued attention and amelioration.

Method: Two characters, a Syrian refugee with limited English proficiency and a black pregnant woman with a history of opioid use disorder, were developed for an online training simulation that includes an interactive life course experience focused on social determinants of health, and a clinical encounter in a community health center utilizing virtual reality immersion.

Ten Open Challenges in Medical Visualization.

The medical domain has been an inspiring application area in visualization research for many years already, but many open challenges remain. The driving forces of medical visualization research have been strengthened by novel developments, for example, in deep learning, the advent of affordable VR technology, and the need to provide medical visualizations for broader audiences. At IEEE VIS 2020, we hosted an Application Spotlight session to highlight recent medical visualization research topics.

Multi-Echo Quantitative Susceptibility Mapping for Strategically Acquired Gradient Echo (STAGE) Imaging.

Purpose: To develop a method to reconstruct quantitative susceptibility mapping (QSM) from multi-echo, multi-flip angle data collected using strategically acquired gradient echo (STAGE) imaging.

Methods: The proposed QSM reconstruction algorithm, referred to as "structurally constrained Susceptibility Weighted Imaging and Mapping" scSWIM, performs an and regularization-based reconstruction in a single step. The unique contrast of the T1 weighted enhanced (T1WE) image derived from STAGE imaging was used to extract reliable geometry constraints to protect the basal ganglia from over-smoothing.

Hierarchical Image Semantics Using Probabilistic Path Propagations for Biomedical Research.

Image segmentation is an important subtask in biomedical research applications, such as estimating the position and shape of a tumor. Unfortunately, advanced image segmentation methods are not widely applied in research applications as they often miss features, such as uncertainty communication, and may lack an intuitive approach for the use of the underlying algorithm. To solve this problem, this paper fuses a fuzzy and a hierarchical segmentation approach together, thus providing a flexible multiclass segmentation method based on probabilistic path propagations.

Compensatory Enlargement of Ossabaw Miniature Swine Coronary Arteries in Diffuse Atherosclerosis.

Studies in human and non-human primates have confirmed the compensatory enlargement or positive remodeling (Glagov phenomenon) of coronary vessels in the presence of focal stenosis. To our knowledge, this is the first study to document arterial enlargement in a metabolic syndrome animal model with diffuse coronary artery disease (DCAD) in the absence of severe focal stenosis. Two different groups of Ossabaw miniature pigs were fed a high fat atherogenic diet for 4 months (Group I) and 12 months (Group II), respectively.

IVUS validation of patient coronary artery lumen area obtained from CT images.

Aims: Accurate computed tomography (CT)-based reconstruction of coronary morphometry (diameters, length, bifurcation angles) is important for construction of patient-specific models to aid diagnosis and therapy. The objective of this study is to validate the accuracy of patient coronary artery lumen area obtained from CT images based on intravascular ultrasound (IVUS).

Methods And Results: Morphometric data of 5 patient CT scans with 11 arteries from IVUS were reconstructed including the lumen cross sectional area (CSA), diameter and length.

CT-based diagnosis of diffuse coronary artery disease on the basis of scaling power laws.

Purpose: To provide proof of concept for a diagnostic method to assess diffuse coronary artery disease (CAD) on the basis of coronary computed tomography (CT) angiography.

Materials And Methods: The study was approved by the Cleveland Clinic Institutional Review Board, and all subjects gave informed consent. Morphometric data from the epicardial coronary artery tree, determined with CT angiography in 120 subjects (89 patients with metabolic syndrome and 31 age- and sex-matched control subjects) were analyzed on the basis of the scaling power law.

Computed tomography-based diagnosis of diffuse compensatory enlargement of coronary arteries using scaling power laws.

Glagov's positive remodelling in the early stages of coronary atherosclerosis often results in plaque rupture and acute events. Because positive remodelling is generally diffused along the epicardial coronary arterial tree, it is difficult to diagnose non-invasively. Hence, the objective of the study is to assess the use of scaling power law for the diagnosis of positive remodelling of coronary arteries based on computed tomography (CT) images.

Vortex visualization in ultra low Reynolds number insect flight.

We present the visual analysis of a biologically inspired CFD simulation of the deformable flapping wings of a dragonfly as it takes off and begins to maneuver, using vortex detection and integration-based flow lines. The additional seed placement and perceptual challenges introduced by having multiple dynamically deforming objects in the highly unsteady 3D flow domain are addressed. A brief overview of the high speed photogrammetry setup used to capture the dragonfly takeoff, parametric surfaces used for wing reconstruction, CFD solver and underlying flapping flight theory is presented to clarify the importance of several unsteady flight mechanisms, such as the leading edge vortex, that are captured visually.

Extraction of morphometry and branching angles of porcine coronary arterial tree from CT images.

The morphometry (diameters, length, and angles) of coronary arteries is related to their function. A simple, easy, and accurate image-based method to seamlessly extract the morphometry for coronary arteries is of significant value for understanding the structure-function relation. Here, the morphometry of large (> or = 1 mm in diameter) coronary arteries was extracted from computed tomography (CT) images using a recently validated segmentation algorithm.

Biophysical model of the spatial heterogeneity of myocardial flow.

The blood flow in the myocardium has significant spatial heterogeneity. The objective of this study was to develop a biophysical model based on detailed anatomical data to determine the heterogeneity of regional myocardial flow during diastole. The model predictions were compared with experimental measurements in a diastolic porcine heart in the absence of vessel tone using nonradioactive fluorescent microsphere measurements.

Validation of image-based method for extraction of coronary morphometry.

An accurate analysis of the spatial distribution of blood flow in any organ must be based on detailed morphometry (diameters, lengths, vessel numbers, and branching pattern) of the organ vasculature. Despite the significance of detailed morphometric data, there is relative scarcity of data on 3D vascular anatomy. One of the major reasons is that the process of morphometric data collection is labor intensive.

Flow patterns in three-dimensional porcine epicardial coronary arterial tree.

The branching pattern of epicardial coronary arteries is clearly three-dimensional, with correspondingly complex flow patterns. The objective of the present study was to perform a detailed hemodynamic analysis using a three-dimensional finite element method in a left anterior descending (LAD) epicardial arterial tree, including main trunk and primary branches, based on computed tomography scans. The inlet LAD flow velocity was measured in an anesthetized pig, and the outlet pressure boundary condition was estimated based on scaling laws.

A novel method for visualization of entire coronary arterial tree.

The complexity of the coronary circulation especially in the deep layers largely evades experimental investigations. Hence, virtual/computational models depicting structure-function relation of the entire coronary vasculature including the deep layer are imperative. In order to interpret such anatomically based models, fast and efficient visualization algorithms are essential.