Man pages for ANTsX/ANTsRNet
Neural networks for medical image processing

AnchorBoxLayer2DAnchor box layer for SSD architecture (2-D).
AnchorBoxLayer3DAnchor box layer for SSD architecture (3-D).
applySuperResolutionModelapplySuperResolutionModel
applySuperResolutionModelPatchapplySuperResolutionModelPatch
basisWarpGenerate a deformable map from basis
ClusteringLayerClustering layer for Deep Embedded Clustering
convertCoordinatesConvert coordinates to/from min/max representation from/to...
createAlexNetModel2D2-D implementation of the AlexNet deep learning architecture.
createAlexNetModel3D3-D implementation of the AlexNet deep learning architecture.
createAutoencoderModelFunction for creating a symmetric autoencoder model.
createConvolutionalAutoencoderModel2DFunction for creating a 2-D symmetric convolutional...
createConvolutionalAutoencoderModel3DFunction for creating a 3-D symmetric convolutional...
createDeepBackProjectionNetworkModel2D2-D implementation of the deep back-projection network.
createDeepBackProjectionNetworkModel3D3-D implementation of the deep back-projection network.
createDeepDenoiseSuperResolutionModel2D2-D implementation of the deep denoise image super resolution...
createDeepDenoiseSuperResolutionModel3D3-D implementation of the deep denoise image super resolution...
createDenoisingAutoEncoderSuperResolutionModel2D2-D implementation of the denoising autoencoder image super...
createDenoisingAutoEncoderSuperResolutionModel3D3-D implementation of the denoising autoencoder image super...
createDenseNetModel2D2-D implementation of the DenseNet deep learning...
createDenseNetModel3D3-D implementation of the DenseNet deep learning...
createDenseUnetModel2D2-D implementation of the dense U-net deep learning...
createDenseUnetModel3D3-D implementation of the dense U-net deep learning...
createEnhancedDeepSuperResolutionModel2D2-D implementation of the EDSR super resolution architecture.
createExpandedSuperResolutionModel2D2-D implementation of the expanded image super resolution...
createExpandedSuperResolutionModel3D3-D implementation of the expanded image super resolution...
createGoogLeNetModel2D2-D implementation of the GoogLeNet deep learning...
createImageSuperResolutionModel2D2-D implementation of the image super resolution deep...
createImageSuperResolutionModel3D3-D implementation of the image super resolution deep...
createResNetModel2D2-D implementation of the ResNet deep learning architecture.
createResNetModel3D3-D implementation of the ResNet deep learning architecture.
createResNetSuperResolutionModel2D2-D implementation of the ResNet image super resolution...
createResNetSuperResolutionModel3D3-D implementation of the ResNet image super resolution...
createResNetWithSpatialTransformerNetworkModel2D2-D implementation of the ResNet deep learning architecture...
createResNetWithSpatialTransformerNetworkModel3D3-D implementation of the ResNet deep learning architecture...
createResUnetModel2D2-D implementation of the Resnet + U-net deep learning...
createResUnetModel3D3-D implementation of the Resnet + U-net deep learning...
createSimpleClassificationWithSpatialTransformerNetworkModel2D2-D implementation of the spatial transformer network.
createSimpleClassificationWithSpatialTransformerNetworkModel3D3-D implementation of the spatial transformer network.
createSsd7Model2D2-D implementation of the SSD 7 deep learning architecture.
createSsd7Model3D3-D implementation of the SSD 7 deep learning architecture.
createSsdModel2D2-D implementation of the SSD deep learning architecture.
createSsdModel3D3-D implementation of the SSD deep learning architecture.
createUnetModel2D2-D implementation of the U-net deep learning architecture.
createUnetModel3D3-D image segmentation implementation of the U-net deep...
createVggModel2D2-D implementation of the VGG deep learning architecture.
createVggModel3D3-D implementation of the VGG deep learning architecture.
createWideResNetModel2D2-D implementation of the Wide ResNet deep learning...
createWideResNetModel3D3-D implementation of the Wide ResNet deep learning...
decodeSsd2DDecoding function for 2-D Y_train
decodeSsd3DDecoding function for 3-D Y_train
decodeUnetDecoding function for Y_predicted
DeepEmbeddedClusteringModelDeep embedded clustering (DEC) model class
drawRectanglesPlotting function for 2-D object detection visualization.
encodeSsd2DEncoding function for 2-D Y_train
encodeSsd3DEncoding function for 3-D Y_train
encodeUnetEncoding function for Y_train
extractImagePatchesExtract 2-D or 3-D image patches.
getMixtureDensityLossFunctionReturns a loss function for the mixture density.
getMixtureDensityMseAccuracyFunctionReturns a MSE accuracy function for the mixture density.
getMixtureDensitySamplingFunctionReturns a sampling function for the mixture density.
getPretrainedNetworkgetPretrainedNetwork
GMSDGradient Magnitude Similarity Deviation
jaccardSimilarityJaccard similarity between two sets of boxes.
L2NormalizationLayer2DL2 2-D normalization layer for SSD300/512 architecture.
L2NormalizationLayer3DL2 3-D normalization layer for SSD300/512 architecture.
loss_multilabel_dice_coefficient_errorMultilabel dice loss function.
loss_peak_signal_to_noise_ratio_errorPeak-signal-to-noise ratio.
loss_pearson_correlation_coefficient_errorPearson correlation coefficient
LossSSDLoss function for the SSD deep learning architecture.
MAEMean absolute error of a single image or between two images.
MixtureDensityNetworkLayerMixture density network layer
mixture_density_network_softmaxSoftmax function for mixture density with temperature...
MSEMean square error of a single image or between two images.
multilabel_dice_coefficientModel loss function for multilabel problems- multilabel dice...
peak_signal_to_noise_ratioPeak-signal-to-noise ratio.
pearson_correlation_coefficientPearson correlation coefficient.
PSNRPeak signal-to-noise ratio between two images.
randomImageTransformAugmentationApply random transforms to a predictor / outcome training...
randomImageTransformBatchGeneratorRandom image transformation batch generator
randomImageTransformParametersAugmentationGenerate transform parameters and transformed images
randomImageTransformParametersBatchGeneratorRandom image transform parameters batch generator
randomlyTransformImageDataRandomly transform image data (optional: with corresponding...
reconstructImageFromPatchesReconstruct image from a list of patches.
resampleTensorResamples a spatial tensor.
ResampleTensorLayerCreates a resampled lambda layer
resampleTensorLikeResamples a tensor.
sampleFromCategoricalDistributionSample from a categorical distribution
sampleFromOutputSample from a distribution
ScaleLayerCustom scale layer
SpatialTransformerLayer2DSpatial transformer layer (2-D)
SpatialTransformerLayer3DSpatial transfomer layer (3-D)
splitMixtureParametersSplits the mixture parameters.
SSIMStructural similarity index (SSI) between two images.
uvaSegUnsupervised variational autoencoder segmentation
uvaSegTrainUnsupervised variational autoencoder training
VanillaGanModelVanilla GAN model interpretation
ANTsX/ANTsRNet documentation built on July 16, 2019, 9:21 a.m.