Advanced Normalization Tools (ANTs)

By Brian B. Avants, Nicholas J. Tustison, Hans J. Johnson. 2020

1,589 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/129115feb8466859479c7c5a3c0e6e55ffa890a2

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Citations in the corpus

Spatial aggregation of holistically‐nested convolutional neural networks for automated pancreas localization and segmentation☆ (2017, methodology): “Previous pancreas segmentation work [3], [2], [4], [5] are all based on performing volumetric multiple atlas registration [8], [9], [10] and executing robust label fusion methods [11], [12], [13] to optimize the per-pixel organ labeling process.”
Large Deformation Diffeomorphic Image Registration with Laplacian Pyramid Networks (2020, methodology): “For SyN, we adopt the official implementation in the ANTs software package [3].”
A review on deep learning in medical image analysis (2021, methodology): “There are many freely available tools [19] and toolkits for medical image registration, such as ANTs [24] and Simple ITK [25].”
Recursive Cascaded Networks for Unsupervised Medical Image Registration (2019, methodology): “No GPU implementation of ANTs or Elastix has been found, nor in previous works [5, 8, 19, 35, 37].”
3D Deep Learning on Medical Images: A Review (2020, methodology): “Compared to the traditional optimization approaches (ANTs [107], Elastix [112] and VoxelMorph-2 [113]), their method was 880 times faster, with state-of-the-art performance.”
FastSurfer - A fast and accurate deep learning based neuroimaging pipeline (2019, neutral): “…few well maintained neuroimage processing pipelines such as FreeSurfer (Fischl et al., 2002), BrainSuite(Shattuck and Leahy, 2002), SPM (Friston et al., 2007), ANTs (Avants et al., 2009), or FSL (Jenkinson et al., 2012) are the only means available to process and evaluate the incoming ﬂ ow of data.”
Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network (2018, methodology): “[25], MRI data were preprocessed before the proposed cascaded neural network was applied.”
The development of aperiodic and periodic resting-state power between early childhood and adulthood: New insights from optically pumped magnetometers (2024, methodology): “For the children, age-specific paediatric templates (Richards et al., 2016) were used, first warping the coordinates of each source in the AAL atlas from standard space to the templates using Advanced Normalization Tools (ANTs; version 2.4.3; Avants et al., 2009).”