Status: In production
Open-source application that assists with the visualization, registration, segmentation, and quantification of medical image data. Development of the Slicer is an ongoing international collaboration project organized by the Surgical Planning Lab at Brigham & Women’s Hospital, an affiliate of Harvard Medical School.
3D Slicer (aka Slicer) can be used to display display and analyze volumetric images, surface reconstructions, and continuum meshes extracted from image data such as CT and MR. In addition, specialized neuroanalysis functionality includes sophisticated diffusion and functional image manipulation, processing of data derived from FreeSurfer analysis, and interface to surgical navigation and therapy systems.
In 2010, 3D Slicer version 3.6 was released incorporating a wide range of modules for both general purpose analysis and custom-built tools to accommodate particular research computing needs. 3D Slicer includes a range of tools for image registration to support scenarios such as aligning scans of the same subject taken at different time points (such as pre-op and post-op) or using different imaging modalities (such as registration CT and MR). Other registration methods support aligning multiple subjects into a common reference space for population studies. Additionally, Slicer supports both detailed manual anatomical segmentation using an image editor and automatic segmentation using techniques derived from computer vision including Expectation Maximization and Level Sets.
One significant example of BIRN-sponsored research is FreeSurfer interoperability with the Query Atlas project. The Query Atlas is functionality within Slicer that displays information about the brain region that is currently under the mouse cursor. This feature facilitates interactive exploration of the data. In addition, Slicer includes a service running in the background to perform web queries based on selected anatomical, functional, and metatdata query terms. The usage scenario is that when the mouse pointer “hovers” over a structure the Query Atlas will run in the background and bring up relevant literature and reference material to help clarify the scientific context of the observed imaging data. The user is be able to augment and refine the anatomy-based search using keywords about the clinical condition of the subject and the scan type and protocol.
