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The Medical Image Analysis Laboratory Super-Resolution ToolKit (MIALSRTK) consists of a set of C++ image processing tools necessary to perform motion-robust super-resolution fetal MRI reconstruction.

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Copyright © 2016-2017 Medical Image Analysis Laboratory, University Hospital Center and University of Lausanne (UNIL-CHUV), Switzerland

This software is distributed under the open-source BSD 3-Clause License. See LICENSE file for details.


DOI

The Medical Image Analysis Laboratory Super-Resolution ToolKit (MIALSRTK) consists of a set of C++ image processing tools necessary to perform motion-robust super-resolution fetal MRI reconstruction. This toolkit, supported by the Swiss National Science Foundation (grant SNSF-141283), includes all algorithms and methods for brain extraction [1], intensity standardization [1,2], motion estimation and super-resolution [2] developed during my PhD. It uses the CMake build system and depends on the open-source image processing Insight ToolKit (ITK) library, the command line parser TCLAP library and OpenMP for multi-threading. The USAGE message of each tool can be obained using either the -h or --help flag.

A Docker image is provided to facilitate the deployment and freely available @ Docker store.

  • Please acknowledge this software in any work reporting results using MIALSRTK by citing the following articles:

[1] S. Tourbier, C. Velasco-Annis, V. Taimouri, P. Hagmann, R. Meuli, S. K. Warfield, M. B. Cuadra, A. Gholipour, Automated template-based brain localization and extraction for fetal brain MRI reconstruction, Neuroimage (2017) In Press. DOI

[2] S. Tourbier, X. Bresson, P. Hagmann, R. Meuli, M. B. Cuadra, An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization, Neuroimage 118 (2015) 584-597. DOI

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  • Sébastien Tourbier (sebastientourbier)

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The Medical Image Analysis Laboratory Super-Resolution ToolKit (MIALSRTK) consists of a set of C++ image processing tools necessary to perform motion-robust super-resolution fetal MRI reconstruction.

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  • C++ 91.2%
  • Python 5.1%
  • CMake 1.8%
  • Shell 1.6%
  • Dockerfile 0.3%