SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data

3D bioprinting of tissues and organs for regenerative medicine.

Background: Statistical shape models are widely used in biomedical research. They are routinely implemented for automatic image segmentation or object identification in medical images. In these fields, however, the acquisition of the large training datasets, required to develop these models, is usually a time-consuming process. Even after this effort, the collections of datasets are often lost or mishandled resulting in replication of work. Objective: To solve these problems, the Virtual Skeleton Database (VSD) is proposed as a centralized storage system where the data necessary to build statistical shape models can be stored and shared. Methods: The VSD provides an online repository system tailored to the needs of the medical research community. The processing of the most common image file types, a statistical shape model framework, and an ontology-based search provide the generic tools to store, exchange, and retrieve digital medical datasets. The hosted data are accessible to the community, and collaborative research catalyzes their productivity. Results: To illustrate the need for an online repository for medical research, three exemplary projects of the VSD are presented: (1) an international collaboration to achieve improvement in cochlear surgery and implant optimization, (2) a population-based analysis of femoral fracture risk between genders, and (3) an online application developed for the evaluation and comparison of the segmentation of brain tumors. Conclusions: The VSD is a novel system for scientific collaboration for the medical image community with a data-centric concept and semantically driven search option for anatomical structures. The repository has been proven to be a useful tool for collaborative model building, as a resource for biomechanical population studies, or to enhance segmentation algorithms. [J Med Internet Res 2013;15(11):e245]

The Virtual Skeleton Database: An Open Access Repository for Biomedical Research and Collaboration

https://physicstoday.scitation.org/doi/pdf/10.1063/PT.3.1721

Reinventing Discovery: The New Era of Networked Science

http://alunevans.info/publications/computers_and_graphics_3d_web_survey_final_preprint.pdf

3D graphics on the web: A survey

Reproducibility verification is essential to the practice of the scientific method. Researchers report their findings, which are strengthened as other independent groups in the scientific community share similar outcomes. In the many scientific fields where software has become a fundamental tool for capturing and analyzing data, this requirement of reproducibility implies that reliable and comprehensive software platforms and tools should be made available to the scientific community. The tools will empower them and the public to verify, through practice, the reproducibility of observations that are reported in the scientific literature.Medical image analysis is one of the fields in which the use of computational resources, both software and hardware, are an essential platform for performing experimental work. In this arena, the introduction of the Insight Toolkit (ITK) in 1999 has transformed the field and facilitates its progress by accelerating the rate at which algorithmic implementations are developed, tested, disseminated and improved. By building on the efficiency and quality of open source methodologies, ITK has provided the medical image community with an effective platform on which to build a daily workflow that incorporates the true scientific practices of reproducibility verification.This article describes the multiple tools, methodologies, and practices that the ITK community has adopted, refined, and followed during the past decade, in order to become one of the research communities with the most modern reproducibility verification infrastructure. For example, 207 contributors have created over 2400 unit tests that provide over 84% code line test coverage. The Insight Journal, an open publication journal associated with the toolkit, has seen over 360,000 publication downloads. The median normalized closeness centrality, a measure of knowledge flow, resulting from the distributed peer code review system was high, 0.46.

/pdf/itk-enabling-reproducible-research-and-open-science-46ofi1px4h.pdf

ITK: enabling reproducible research and open science

In scientific visualization, data are becoming more and more important and usually implies a cooperative effort. Moreover experts are usually geographically distributed, therefore they need collaborative tools to work efficiently. To solve this limitation, a prospective action has been recently initiated, with the development of a web based application for collaborative interaction based on two innovating technologies: WebGL and WebSocket. To demonstrate this approach, a prototype has been developed based on the Visible Patient project. In this paper we present the architecture of the proposed system, the initial implementation experiment and a comparison with current technologies. Finally we discuss the future work and potential improvements.

Real-time collaborative scientific WebGL visualization with WebSocket

In the recent years, the scientific community has been focusing on the management and dissemination of datasets. Challenged by the rapid growth in the number and size of scientific data and supported by new governmental policies, data sharing has become a necessary step in scientific discovery. In parallel, publishing companies have shifted their business to provide not only publications but also associated datasets to their readers. In fact, the publishing industry has been investigating ways to disseminate datasets and more importantly, to present this data to readers in a meaningful manner. In this paper, we present a combination of two leading technologies which allows for online exploration and visualization of scientific datasets. We have combined a digital archiving system, MIDAS, with an online parallel visualization framework, ParaViewWeb. The system has been deployed at several organizations and has been proven to facilitate knowledge dissemination across scientific teams.

/pdf/remote-visualization-of-large-datasets-with-midas-and-2khfongns0.pdf

Remote visualization of large datasets with MIDAS and ParaViewWeb

In this paper, we present MIDAS, a web-based digital archiving system that processes large collections of data. Medical imaging research often involves interdisciplinary teams, each performing a separate task, from acquiring datasets to analyzing the processing results. Moreover, the number and size of the datasets continue to increase every year due to recent advancements in acquisition technology. As a result, many research laboratories centralize their data and rely on distributed computing power. We created a web-based digital archiving repository based on openstandards. The MIDAS repository is specifically tuned for medical and scientific datasets and provides a flexible data management facility, a search engine, and an online image viewer. MIDAS enables users to run a set of extensible image processing algorithms from the web to the selected datasets and to add new algorithms to the MIDAS system, facilitating the dissemination of users' work to different research partners. The MIDAS system is currently running in several research laboratories and has demonstrated its ability to streamline the full image processing workflow from data acquisition to image analysis and reports.

A Digital Archiving System and Distributed Server-side processing of Large Datasets

Nowadays, 3D visualization is part of our everyday lives and remains an important tool for understanding complex structures, dynamic simulations, and research discoveries. In the meantime, the complexity of the visualization often requires specific hardware, including visualization clusters, as well as dedicated software tools. Several efforts, such as WebGL and remote visualization, have been pushing visualization to the web browser. However, technical limitations have constrained the adoption of web browsers as a means of rendering 3D datasets. To surpass these limitations, prospective action has been recently initiated with the development of a web application based on two innovative technologies: WebGL and ParaViewWeb. This application combines the benefits of local and remote rendering, therefore allowing a user to visualize small to massive 3D molecular datasets on a large number of devices. To demonstrate this approach a prototype has been developed, and in this paper we present the hybrid architecture of the proposed system, the initial implementation experiment, and a comparison with current technologies. Finally, we discuss the future work and potential improvements of the application.

Charles Marion

Papers

ITK: enabling reproducible research and open science

Real-time collaborative scientific WebGL visualization with WebSocket

Remote visualization of large datasets with MIDAS and ParaViewWeb

A Digital Archiving System and Distributed Server-side processing of Large Datasets

A hybrid visualization system for molecular models