The need for such an image-viewer stemmed from an ongoing project in our lab which involved the organization and curation of large retrospectively-collected imaging data sets of cancer patients with high grade gliomas.
#K pacs viewer online Offline
We will review various tools currently available that support this functionality offline as well as demonstrate our current work that allows visualization of image overlays directly via HTML.Ĭapitalizing on these recent advances, we have developed a light weight HTML based image browser that integrates XNAT, a popular research informatics platform which we will describe later. We will therefore also review some tools and frameworks that support imaging formats in addition to DICOM.Ī number of emerging technologies allow visualization and interaction with not only the image itself, but also with derivative images such as masks, tractography results, and statistical maps. While DICOM is the lingua franca of clinical imaging, it is worth noting many other imaging formats are commonly used in imaging research. In this work, we review some of the existing source tools and libraries that facilitate web-based image visualization of imaging data sets. However, recent advances in web-based technologies such as HTML5 and faster overall internet connectivity have the potential to significantly simplify this process. These inefficient ad hoc solutions often make collaboration and soliciting feedback on imaging data complicated, imprecise, and time intensive.
#K pacs viewer online software
Visualization and sharing of complex imaging data sets has traditionally involved downloading large file sets, installing custom software applications, or in some cases simply sharing screenshots of specific images with colleagues for review and comment. Its zero-footprint design allows the user to connect to XNAT from a web browser, navigate through projects, experiments, and subjects, and view DICOM images with accompanying metadata all within a single viewing instance.ĭata management challenges regularly pose problems among imaging laboratories. XNATView was developed to simplify quality assurance, help organize imaging data, and facilitate data sharing for intra- and inter-laboratory collaborations. It consists of a PyXNAT-based framework to wrap around the REST application programming interface (API) and query the data in XNAT.
#K pacs viewer online archive
XNATView is a light framework recently developed in our lab to visualize DICOM images stored in The Extensible Neuroimaging Archive Toolkit (XNAT). This allows centralization of file storage and facilitates image review and analysis.