ColocZStats: a z-stack signal colocalization extension tool for 3D slicer.

Confocal microscopy has evolved to be a widely adopted imaging technique in molecular biology and is frequently utilized to achieve accurate subcellular localization of proteins. Applying colocalization analysis on image z-stacks obtained from confocal fluorescence microscopes is a dependable method of revealing the relationship between different molecules. In addition, despite the established advantages and growing adoption of 3D visualization software in various microscopy research domains, there have been few systems that can support colocalization analysis within a user-specified region of interest (ROI).

SmartVR Pointer: Using Smartphones and Gaze Orientation for Selection and Navigation in Virtual Reality.

Some of the barriers preventing virtual reality (VR) from being widely adopted are the cost and unfamiliarity of VR systems. Here, we propose that in many cases, the specialized controllers shipped with most VR head-mounted displays can be replaced by a regular smartphone, cutting the cost of the system, and allowing users to interact in VR using a device they are already familiar with. To achieve this, we developed SmartVR Pointer, an approach that uses smartphones to replace the specialized controllers for two essential operations in VR: selection and navigation by teleporting.

Novel segmentation algorithm for high-throughput analysis of spectral domain-optical coherence tomography imaging of teleost retinas.

Spectral domain-optical coherence tomography (SD-OCT) has become an essential tool for assessing ocular tissues in live subjects and conducting research on ocular development, health, and disease. The processing of SD-OCT images, particularly those from non-mammalian species, is a labor-intensive manual process due to a lack of automated analytical programs. This paper describes the development and implementation of a novel computer algorithm for the quantitative analysis of SD-OCT images of live teleost eyes.

Use of Extended Reality in Medical Education: An Integrative Review.

Unlabelled: Extended reality (XR) has emerged as an innovative simulation-based learning modality. An integrative review was undertaken to explore the nature of evidence, usage, and effectiveness of XR modalities in medical education. One hundred and thirty-three ( = 133) studies and articles were reviewed.

Augmented Reality as a Telemedicine Platform for Remote Procedural Training.

Traditionally, rural areas in many countries are limited by a lack of access to health care due to the inherent challenges associated with recruitment and retention of healthcare professionals. Telemedicine, which uses communication technology to deliver medical services over distance, is an economical and potentially effective way to address this problem. In this research, we develop a new telepresence application using an Augmented Reality (AR) system.

GeNET: a web application to explore and share Gene Co-expression Network Analysis data.

Gene Co-expression Network Analysis (GCNA) is a popular approach to analyze a collection of gene expression profiles. GCNA yields an assignment of genes to gene co-expression modules, a list of gene sets statistically over-represented in these modules, and a gene-to-gene network. There are several computer programs for gene-to-gene network visualization, but these programs have limitations in terms of integrating all the data generated by a GCNA and making these data available online.

OMARC: An online multimedia application for training health care providers in the assessment of respiratory conditions.

Objectives: OMARC, a multimedia application designed to support the training of health care providers for the identification of common lung sounds heard in a patient's thorax as part of a health assessment, is described and its positive contribution to user learning is assessed. The main goal of OMARC is to effectively help health-care students become familiar with lung sounds as part of the assessment of respiratory conditions. In addition, the application must be easy to use and accessible to students and practitioners over the internet.

Integrative visualization of temporally varying medical image patterns.

We have developed a tool for the visualization of temporal changes of disease patterns, using stacks of medical images collected in time-series experiments. With this tool, users can generate 3D surface models representing disease patterns and observe changes over time in size, shape, and location of clinically significant image patterns. Statistical measurements of the volume of the observed disease patterns can be performed simultaneously.

Estimating cell count and distribution in labeled histological samples using incremental cell search.

Cell proliferation is critical to the outgrowth of biological structures including the face and limbs. This cellular process has traditionally been studied via sequential histological sampling of these tissues. The length and tedium of traditional sampling is a major impediment to analyzing the large datasets required to accurately model cellular processes.

Generation of connectivity-preserving surface models of multiple sclerosis lesions.

Progression of multiple sclerosis (MS) results in brain lesions caused by white matter inflammation. MS lesions have various shapes, sizes and locations, affecting cognitive abilities of patients to different extents. To facilitate the visualization of the brain lesion distribution, we have developed a software tool to build 3D surface models of MS lesions.

Building generic anatomical models using virtual model cutting and iterative registration.

Background: Using 3D generic models to statistically analyze trends in biological structure changes is an important tool in morphometrics research. Therefore, 3D generic models built for a range of populations are in high demand. However, due to the complexity of biological structures and the limited views of them that medical images can offer, it is still an exceptionally difficult task to quickly and accurately create 3D generic models (a model is a 3D graphical representation of a biological structure) based on medical image stacks (a stack is an ordered collection of 2D images).

An efficient virtual dissection tool to create generic models for anatomical atlases.

We have developed an efficient virtual dissection tool to create generic 3D models for anatomical atlases without the need for artistic drawings. Our custom-developed tool can be used to extract 3D models from 2D medical image stacks, cut the models and align the sub-models. Corresponding 2D medical image portions of the sub-models can then be registered and averaged.

Fast interactive integration of cross-sectional image datasets and surface data for morphometric analysis.

To investigate external facial morphology and cell proliferation patterns and their relationship with cleft lip malformation in mice, we need to compare samples of mice tissue photographs and surface reconstructions from micro-CT scans obtained from mouse embryos. Tissue samples obtained through digital photography are typically misaligned with respect to each other, which prevents further analysis. We have developed a system for fast interactive alignment of these image stacks for volume reconstruction and data visualization and analysis in 3D.