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

abernard102@gmail.com 2013-12-02

Summary:

Use the link to access the ful text article from the Journal of Medical Internet Research.  The abstract reads as follows: "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."

Link:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3841349/

From feeds:

Open Access Tracking Project (OATP) » abernard102@gmail.com

Tags:

oa.new oa.gold oa.green oa.open_science oa.biomedicine oa.virtual_skeleton_database oa.repositories oa.journals

Date tagged:

12/02/2013, 07:35

Date published:

12/02/2013, 02:35