Medical image analysis framework merging ANTsR and deep learning
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A collection of deep learning architectures ported to the R language and tools for basic medical image processing.

Examples available at ANTsRNetExamples.

Documentation page


Image voxelwise segmentation/regression

Image classification/regression

Object detection

Image super-resolution

Registration and transforms


  • ANTsRNet Installation:
    • Option 1:
      $ R
      > devtools::install_github( "ANTsX/ANTsRNet" )
    • Option 2:
      $ git clone


  • Nicholas J. Tustison, Brian B. Avants, Zixuan Lin, Xue Feng, Nicholas Cullen, Jaime F. Mata, Lucia Flors, James C. Gee, Talissa A. Altes, John P. Mugler III, and Kun Qing. Convolutional Neural Networks with Template-Based Data Augmentation for Functional Lung Image Quantification, Academic Radiology. (pubmed)

  • Andrew T. Grainger, Nicholas J. Tustison, Kun Qing, Rene Roy, Stuart S. Berr, and Weibin Shi. Deep learning-based quantification of abdominal fat on magnetic resonance images. PLoS One, 13(9):e0204071, Sep 2018. (pubmed)

  • Cullen N.C., Avants B.B. (2018) Convolutional Neural Networks for Rapid and Simultaneous Brain Extraction and Tissue Segmentation. In: Spalletta G., Piras F., Gili T. (eds) Brain Morphometry. Neuromethods, vol 136. Humana Press, New York, NY doi