Background
A brief history of Nirfast:
Nirfast was originally developed in 2001 as a MATLAB-based package used to model near-infrared light propagation through tissue and reconstruct images of optical biomarkers. As research in optical imaging advanced, many of these major innovations where introduced in the field and included in the NIRFAST software. For example, coupling an optical image system with conventional medical imaging modalities to enable multi-model "spacial priors" imaging.
In the early 2010s, NIRFAST developers introduced a major update
to the software by releasing a vtk-based user interface to import
medical images (DICOMS) from conventional imaging systems (MRI,
CT, etc.), segment those images into tissue regions, create
NIRFAST-compatible finite element meshes, and use those meshes to
reconstruct images of optical biomarkers. While closely linked,
users still had to download the image processing front-end (called
"NIRView") and MATLAB-based optical computation packages
(called "NIRFAST") separately.
March, 2016: NIRFASTSlicer
NIRFASTSlicer is the latest version of NIRFAST (now available for download), and marks another major milestone for the NIRFAST project. NIRFASTSlicer integrates the traditional NIRFAST optical computation engine (MATLAB code) into a customised version of 3DSlicer, which now handles all of the medical image processing/analysis tasks (replacing NIRView). 3DSlicer is an open-source medical image processing software package, well known in the medical imaging research community. It is maintained by a large community of developers, is highly extensible, and facilitates creation of custom versions for specific applications. In addition to offering a stable, well-maintained platform with cutting edge imaging processing tools for the NIRFAST workflow, this update also provides a single installer.April, 2021: NIRFASTer
Taking full advantage of heterogenous computing capabilities of modern computers, NIRFAST has been re-engineered to utilise both multi-threading and GPU capabilities without the need of additional MATLAB toolboxes: specifically, the main models of NIRFAST have been developed utilising custom developed mex files, allowed utilisation of multiple cores, and where available, Nvidia GPU multi-threading.March, 2018: Major update released as NIRFASTSlicer 2.0 and NIRFASTMatlab 9.1
This release introduced:
1
A much more sophisticated and user-friendly set of
segmentation tools.
2
3
NIRFASTMatlab was unbundled from NIRFASTSlicer to make project management more efficient.