GRAPE: a graphical pipeline environment for image analysis in adaptive magnetic resonance imaging

Int J Comput Assist Radiol Surg. 2017 Mar;12(3):449-457. doi: 10.1007/s11548-016-1495-z. Epub 2016 Oct 28.

Abstract

Purpose: We present a platform, GRAphical Pipeline Environment (GRAPE), to facilitate the development of patient-adaptive magnetic resonance imaging (MRI) protocols.

Methods: GRAPE is an open-source project implemented in the Qt C++ framework to enable graphical creation, execution, and debugging of real-time image analysis algorithms integrated with the MRI scanner. The platform provides the tools and infrastructure to design new algorithms, and build and execute an array of image analysis routines, and provides a mechanism to include existing analysis libraries, all within a graphical environment. The application of GRAPE is demonstrated in multiple MRI applications, and the software is described in detail for both the user and the developer.

Results: GRAPE was successfully used to implement and execute three applications in MRI of the brain, performed on a 3.0-T MRI scanner: (i) a multi-parametric pipeline for segmenting the brain tissue and detecting lesions in multiple sclerosis (MS), (ii) patient-specific optimization of the 3D fluid-attenuated inversion recovery MRI scan parameters to enhance the contrast of brain lesions in MS, and (iii) an algebraic image method for combining two MR images for improved lesion contrast.

Conclusions: GRAPE allows graphical development and execution of image analysis algorithms for inline, real-time, and adaptive MRI applications.

Keywords: Advanced computing; Graphical user interface; Patient-specific imaging; Real-time; Visual programming.

MeSH terms

  • Algorithms*
  • Brain / diagnostic imaging*
  • Computer Graphics
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Magnetic Resonance Imaging / methods*
  • Multiple Sclerosis / diagnostic imaging*
  • Software
  • User-Computer Interface