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] }, { "page": "apply", "title": "Extension of apply to allow input of antsImage", "topics": [ "apply", "apply.antsImage", "apply.default" ] }, { "page": "apply_simlr_matrices", "title": "Apply SIMLR projection matrices with r01.1-style versioning", "topics": [ "apply_simlr_matrices" ] }, { "page": "apply_simlr_matrices_dtfix", "title": "Apply simlr matrices to an existing data frame and combine the results with DTI naming fix.", "topics": [ "apply_simlr_matrices_dtfix" ] }, { "page": "apply_transform_matrix", "title": "Apply a learned transform to a new matrix", "topics": [ "apply_transform_matrix" ] }, { "page": "applyAntsrTransform", "title": "applyAntsrTransform", "topics": [ "applyAntsrTransform" ] }, { "page": "applyAntsrTransformToImage", "title": "applyAntsrTransformToImage", "topics": [ "applyAntsrTransformToImage" ] }, { "page": "applyAntsrTransformToPoint", "title": "applyAntsrTransformToPoint", "topics": [ "applyAntsrTransformToPoint" ] }, { "page": "applyAntsrTransformToVector", "title": "applyAntsrTransformToVector", "topics": [ "applyAntsrTransformToVector" ] }, { "page": "as.antsImage", "title": "Convert Objects into antsImage objects", "topics": [ "as.antsImage", "as.antsImage,array-method", "as.antsImage,matrix-method" ] }, { "page": "as.antsMatrix", "title": "Coerce Object to as.antsMatrix", "topics": [ "as.antsMatrix", "as.antsMatrix,data.frame-method", "as.antsMatrix,list-method", "as.antsMatrix,matrix-method" ] }, { "page": "as.array", "title": "Coerce antsImage objects to array", "topics": [ "as.array", "as.array,antsImage-method", "as.array.antsImage", "as.character.antsImage", "as.data.frame,antsMatrix-method", "as.data.frame.antsMatrix", "as.factor.antsImage", "as.list,antsMatrix-method", "as.matrix,antsImage-method", "as.matrix,antsMatrix-method", "as.matrix.antsImage", "as.numeric,antsImage-method", "dim,antsImage-method", "factor.antsImage" ] }, { "page": "aslAveraging", "title": "Average ASL tag-control pairs to estimate perfusion", "topics": [ "aslAveraging" ] }, { "page": "aslCensoring", "title": "Censor bad volumes from ASL data.", "topics": [ "aslCensoring" ] }, { "page": "aslDenoiseR", "title": "WIP: data-driven denoising for ASL MRI", "topics": [ "aslDenoiseR" ] }, { "page": "aslPerfusion", "title": "ASL-based Perfusion from PASL, CASL or pCASL.", "topics": [ "aslPerfusion" ] }, { "page": "atropos", "title": "FMM Segmentation", "topics": [ "atropos" ] }, { "page": "ba_svd", "title": "Robust SVD with Automatic rsvd Fallback", "topics": [ "ba_svd" ] }, { "page": "backup_simlr", "title": "backup simlr implementation", "topics": [ "backup_simlr" ] }, { "page": "basal_forebrain", "title": "basal_forebrain", "topics": [ "basal_forebrain" ] }, { "page": "basicInPaint", "title": "Inpaints missing imaging data from boundary data", "topics": [ "basicInPaint" ] }, { "page": "bayesianCBF", "title": "Uses probabilistic segmentation to constrain pcasl-based cbf computation.", "topics": [ "bayesianCBF" ] }, { "page": "bayesianlm", "title": "Simple bayesian regression function.", "topics": [ "bayesianlm" ] }, { "page": "bigLMStats", "title": "Efficiently compute basic statistical inference from regressions with multiple outcomes", "topics": [ "bigLMStats" ] }, { "page": "blockStimulus", "title": "Block stimulus model for FMRI Data", "topics": [ "blockStimulus" ] }, { "page": "bloodPerfusionSVD", "title": "Calculate blood perfusion using deconvolution.", "topics": [ "bloodPerfusionSVD" ] }, { "page": "bold_correlation_matrix", "title": "BOLD Correlation Matrix", "topics": [ "bold_correlation_matrix" ] }, { "page": "boxplot.antsImage", "title": "Boxplot of Values in an Image", "topics": [ "boxplot.antsImage" ] }, { "page": "buildTemplate", "title": "ANTs template building.", "topics": [ "buildTemplate" ] }, { "page": "calculate_simlr_energy", "title": "Calculate SiMLR energy for optimization", "topics": [ "calculate_simlr_energy" ] }, { "page": "calculate_simlr_gradient", "title": "Calculate SiMLR Similarity Gradient", "topics": [ "calculate_simlr_gradient" ] }, { "page": "cerebellum", "title": "cerebellum", "topics": [ "cerebellum" ] }, { "page": "cerebellum_labels", "title": "cerebellum_labels", "topics": [ "cerebellum_labels" ] }, { "page": "check_ants-methods", "title": "Check if antsImage or read in", "topics": [ "check_ants", "check_ants,antsImage-method", "check_ants,ANY-method", "check_ants,character-method", "check_ants,list-method", "check_ants-methods" ] }, { "page": "check_zero_variance", "title": "Check a matrix for zero-variance rows and columns", "topics": [ "check_zero_variance" ] }, { "page": "cit168_brainstem", "title": "cit168_brainstem", "topics": [ "cit168_brainstem" ] }, { "page": "cit168_reinf_learn", "title": "cit168_reinf_learn", "topics": [ "cit168_reinf_learn" ] }, { "page": "CIT168_Reinf_Learn_v1_label_descriptions_pad", "title": "CIT168 reinforcement learning atlas label descriptions", "topics": [ "CIT168_Reinf_Learn_v1_label_descriptions_pad" ] }, { "page": "CIT168_T1w_700um_pad_adni_brainstem", "title": "CIT168 T1w 700um pad adni brainstem", "topics": [ "CIT168_T1w_700um_pad_adni_brainstem" ] }, { "page": "clip_gradient_by_quantile", "title": "Clip a Gradient Matrix by a Quantile of its Values", "topics": [ "clip_gradient_by_quantile" ] }, { "page": "clip_gradient_norm", "title": "Clip a Gradient Matrix by its Frobenius Norm", "topics": [ "clip_gradient_norm" ] }, { "page": "clusterTimeSeries", "title": "Split time series image into k distinct images", "topics": [ "clusterTimeSeries" ] }, { "page": "coerce_mask", "title": "Simple Mask Maker", "topics": [ "coerce_mask" ] }, { "page": "combineNuisancePredictors", "title": "Combine and reduce dimensionality of nuisance predictors.", "topics": [ "combineNuisancePredictors" ] }, { "page": "compcor", "title": "Compcors the input matrix using SVD and returns the result.", "topics": [ "compcor" ] }, { "page": "composeAntsrTransforms", "title": "composeAntsrTransforms", "topics": [ "composeAntsrTransforms" ] }, { "page": "composeDisplacementFields", "title": "composeDisplacementFields", "topics": [ "composeDisplacementFields" ] }, { "page": "composeTransformsToField", "title": "Compose arbitrary transform list into a deformation field.", "topics": [ "composeTransformsToField" ] }, { "page": "compute_communalities", "title": "Compute Communalities from Factor Scores", "topics": [ "compute_communalities" ] }, { "page": "compute_variance_explained_per_factor", "title": "Compute Variance Explained per Factor", "topics": [ "compute_variance_explained_per_factor" ] }, { "page": "computeDVARS", "title": "computeDVARS", "topics": [ "computeDVARS" ] }, { "page": "computeDVARSspatialMap", "title": "computeDVARSspatialMap", "topics": [ "computeDVARSspatialMap" ] }, { "page": "construct_sim_names", "title": "Construct SiMLR Feature Names", "topics": [ "construct_sim_names" ] }, { "page": "convolveImage", "title": "convolve one image with another", "topics": [ "convolveImage" ] }, { "page": "corw", "title": "produces a correlation matrix via weighted correlation.", "topics": [ "corw" ] }, { "page": "create_optimizer", "title": "Create and Initialize a SIMLR Optimizer", "topics": [ "create_optimizer" ] }, { "page": "createAntsrTransform", "title": "createAntsrTransform", "topics": [ "createAntsrTransform" ] }, { "page": "createJacobianDeterminantImage", "title": "createJacobianDeterminantImage", "topics": [ "createJacobianDeterminantImage" ] }, { "page": "createWarpedGrid", "title": "Create a warped grid for visualization.", "topics": [ "createWarpedGrid" ] }, { "page": "cropImage", "title": "crop a sub-image via a mask", "topics": [ "cropImage" ] }, { "page": "cropImageCenter", "title": "Crop the center of an image.", "topics": [ "cropImageCenter" ] }, { "page": "cropImageFromCenterPoint", "title": "Crop a patch from an image around a center point", "topics": [ "cropImageFromCenterPoint" ] }, { "page": "cropIndices", "title": "crop a sub-image by image indices", "topics": [ "cropIndices" ] }, { "page": "crossvalidatedR2", "title": "Cross-Validated R^2 value", "topics": [ "crossvalidatedR2" ] }, { "page": "cut.antsImage", "title": "Perform Cut on an image", "topics": [ "cut.antsImage" ] }, { "page": "cvEigenanatomy", "title": "Cross-validation method for eigenanatomy decompositions.", "topics": [ "cvEigenanatomy" ] }, { "page": "dataAugmentation", "title": "Randomly transform image data.", "topics": [ "dataAugmentation" ] }, { "page": "decode_pymm_names", "title": "Decode ANTsPyMM technical shorthand to legible anatomical names", "topics": [ "decode_pymm_names" ] }, { "page": "deconvolutionSVD", "title": "Regularize SVD (deconvolution) solution of cerebral blood flow.", "topics": [ "deconvolutionSVD" ] }, { "page": "decropImage", "title": "decrop a sub-image back into the full image", "topics": [ "decropImage" ] }, { "page": "denoiseImage", "title": "Denoise an image", "topics": [ "denoiseImage" ] }, { "page": "density.antsImage", "title": "Density of Values in an Image", "topics": [ "density.antsImage" ] }, { "page": "DesikanKillianyTourville", "title": "DesikanKillianyTourville", "topics": [ "DesikanKillianyTourville" ] }, { "page": "dice_overlap_soft_matrix", "title": "Compute pairwise Dice overlaps for matrix rows or columns", "topics": [ "dice_overlap_soft_matrix" ] }, { "page": "dice_overlap_soft_vector", "title": "Compute Dice overlap for sparse vectors with optional quantile thresholding", "topics": [ "dice_overlap_soft_vector" ] }, { "page": "displacementFieldFromAntsrTransform", "title": "displacementFieldFromAntsrTransform", "topics": [ "displacementFieldFromAntsrTransform" ] }, { "page": "divide_by_column_sum", "title": "Divide each column by the sum of column absolute values", "topics": [ "divide_by_column_sum" ] }, { "page": "dkt", "title": "dkt", "topics": [ "dkt" ] }, { "page": "dkt_cit_labels", "title": "dkt_cit_labels", "topics": [ "dkt_cit_labels" ] }, { "page": "dkt_cortex_cit_deep_brain", "title": "dkt cortex cit deep brain", "topics": [ "dkt_cortex_cit_deep_brain" ] }, { "page": "dkt_labels", "title": "dkt_labels", "topics": [ "dkt_labels" ] }, { "page": "dlbs", "title": "dlbs", "topics": [ "dlbs" ] }, { "page": "eanatDef", "title": "Eigenanatomy with deflation", "topics": [ "eanatDef" ] }, { "page": "eanatSelect", "title": "Selection of n eigenvectors and sparsity for eigenanatomy", "topics": [ "eanatSelect" ] }, { "page": "eigSeg", "title": "Segmentation for eigenanatomy.", "topics": [ "eigSeg" ] }, { "page": "ensembled_sparsity", "title": "Create a Smoothed Sparse Matrix via Permutation Ensemble Averaging", "topics": [ "ensembled_sparsity" ] }, { "page": "error_not_antsImage", "title": "Stop if not an antsImage object", "topics": [ "error_not_antsImage" ] }, { "page": "estimate_joint_rank", "title": "Estimate the Joint Rank of a Multi-View Dataset via Parallel Analysis", "topics": [ "estimate_joint_rank" ] }, { "page": "estimate_learning_rate_nsa", "title": "Estimate Robust Learning Rate for NSA-Flow", "topics": [ "estimate_learning_rate_nsa" ] }, { "page": "estimate_rank_by_permutation_rv", "title": "Estimate Joint Rank via Cross-View RV Analysis", "topics": [ "estimate_rank_by_permutation_rv" ] }, { "page": "estSmooth", "title": "Estimate image smoothness", "topics": [ "estSmooth" ] }, { "page": "euler", "title": "Euler Character", "topics": [ "euler" ] }, { "page": "exemplarInpainting", "title": "Uses example images to inpaint or approximate an existing image.", "topics": [ "exemplarInpainting" ] }, { "page": "exploratory_visualization", "title": "Exploratory Clustering and Visualization", "topics": [ "exploratory_visualization" ] }, { "page": "extend_simlr_embedding_with_new_modalities", "title": "Extend an existing SIMLR embedding with new modality blocks", "topics": [ "extend_simlr_embedding_with_new_modalities" ] }, { "page": "extractImagePatchCoordinates", "title": "Extract 2-D or 3-D image patch coordinates.", "topics": [ "extractImagePatchCoordinates" ] }, { "page": "extractImagePatches", "title": "Extract 2-D or 3-D image patches.", "topics": [ "extractImagePatches" ] }, { "page": "extractSlice", "title": "extract a slice from an image", "topics": [ "extractSlice" ] }, { "page": "FA_JHU_labels_edited", "title": "FA JHU labels edited", "topics": [ "FA_JHU_labels_edited" ] }, { "page": "fast_whiten", "title": "Fast Matrix Whitening", "topics": [ "fast_whiten" ] }, { "page": "fastMarchingExtension", "title": "Fast Marching Extension filter will extend an intensity or label image from a known region into the unknown region along a geodesic path", "topics": [ "fastMarchingExtension" ] }, { "page": "filterfMRIforNetworkAnalysis", "title": "Basic pre-processing for BOLD or ASL-based network analysis.", "topics": [ "filterfMRIforNetworkAnalysis" ] }, { "page": "fitBsplineDisplacementField", "title": "fitBsplineDisplacementField", "topics": [ "fitBsplineDisplacementField" ] }, { "page": "fitBsplineObjectToScatteredData", "title": "fitBsplineObjectToScatteredData", "topics": [ "fitBsplineObjectToScatteredData" ] }, { "page": "fitThinPlateSplineDisplacementField", "title": "fitThinPlateSplineDisplacementField", "topics": [ "fitThinPlateSplineDisplacementField" ] }, { "page": "fitTimeVaryingTransformToPointSets", "title": "fitTimeVaryingTransformToPointSets", "topics": [ "fitTimeVaryingTransformToPointSets" ] }, { "page": "fitTransformToPairedPoints", "title": "fitTransformToPairedPoints", "topics": [ "fitTransformToPairedPoints" ] }, { "page": "fMRINormalization", "title": "Multi-run normalization, filtering and nuisance estimation for fMRI.", "topics": [ "fMRINormalization" ] }, { "page": "frequencyFilterfMRI", "title": "Band pass filtering for BOLD image.", "topics": [ "frequencyFilterfMRI" ] }, { "page": "frob", "title": "Frobenius Norm of a Matrix", "topics": [ "frob" ] }, { "page": "fsl2antsrTransform", "title": "fsl2antsrTransform", "topics": [ "fsl2antsrTransform" ] }, { "page": "functionalLungSegmentation", "title": "Ventilation-based segmentation of hyperpolarized gas lung MRI.", "topics": [ "functionalLungSegmentation" ] }, { "page": "fusedRidge", "title": "Manifold-Regularized Fused Ridge Regression", "topics": [ "fusedRidge" ] }, { "page": "fusedRidgeDirect", "title": "Direct Manifold-Regularized Fused Ridge Regression (General)", "topics": [ "fusedRidgeDirect" ] }, { "page": "fusedRidgeTorch", "title": "PyTorch-Based Manifold-Regularized Fused Ridge Regression", "topics": [ "fusedRidgeTorch" ] }, { "page": "fuzzySpatialCMeansSegmentation", "title": "fuzzySpatialCMeansSegmentation", "topics": [ "fuzzySpatialCMeansSegmentation" ] }, { "page": "generate_structured_multiview_data", "title": "Generate a Sophisticated Simulated Multi-View Dataset", "topics": [ "generate_structured_multiview_data" ] }, { "page": "generateAifMaskImage", "title": "Automatically generate an arterial input function mask.", "topics": [ "generateAifMaskImage" ] }, { "page": "geoSeg", "title": "brain segmentation based on geometric priors", "topics": [ "geoSeg" ] }, { "page": "getANTsRData", "title": "getANTsRData", "topics": [ "getANTsRData" ] }, { "page": "getAntsrTransformFixedParameters", "title": "getAntsrTransformFixedParameters", "topics": [ "getAntsrTransformFixedParameters" ] }, { "page": "getAntsrTransformParameters", "title": "getAntsrTransformParameters", "topics": [ "getAntsrTransformParameters" ] }, { "page": "getASLNoisePredictors", "title": "Get nuisance predictors from ASL images", "topics": [ "getASLNoisePredictors" ] }, { "page": "getAverageOfTimeSeries", "title": "getAverageOfTimeSeries", "topics": [ "getAverageOfTimeSeries" ] }, { "page": "getCenterOfMass", "title": "center of mass", "topics": [ "getCenterOfMass" ] }, { "page": "getCentroids", "title": "Convert an image to the geometric centroids of its signal", "topics": [ "getCentroids" ] }, { "page": "getfMRInuisanceVariables", "title": "Extract generic fMRI nuisance variables for ASL or BOLD", "topics": [ "getfMRInuisanceVariables" ] }, { "page": "getMask", "title": "Get Mask", "topics": [ "getMask" ] }, { "page": "getMultiResFeatureMatrix", "title": "build multiple resolution predictor matrix from feature images", "topics": [ "getMultiResFeatureMatrix" ] }, { "page": "getMultivariateTemplateCoordinates", "title": "Label multivariate components by an anatomical coordinate system.", "topics": [ "getMultivariateTemplateCoordinates" ] }, { "page": "getNamesFromDataframe", "title": "Extract column names with concatenated search parameters", "topics": [ "getNamesFromDataframe" ] }, { "page": "getNeighborhoodAtVoxel", "title": "Get a hypercube neighborhood at a voxel", "topics": [ "getNeighborhoodAtVoxel" ] }, { "page": "getNeighborhoodInMask", "title": "Get neighborhoods for voxels within mask", "topics": [ "getNeighborhoodInMask" ] }, { "page": "getPixels", "title": "Get Pixels", "topics": [ "getPixels" ] }, { "page": "getTemplateCoordinates", "title": "Define an anatomical coordinate system in a new image based on a template", "topics": [ "getTemplateCoordinates" ] }, { "page": "glm_impute", "title": "Impute missing data using GLM models", "topics": [ "glm_impute" ] }, { "page": "gradient_invariant_orthogonality_defect", "title": "Compute the Gradient of the Orthogonality Defect", "topics": [ "gradient_invariant_orthogonality_defect" ] }, { "page": "gradient_invariant_orthogonality_salad", "title": "Gradient of the Invariant Orthogonality Defect Measure", "topics": [ "gradient_invariant_orthogonality_salad" ] }, { "page": "hausdorffDistance", "title": "hausdorffDistance", "topics": [ "hausdorffDistance" ] }, { "page": "hemisphere", "title": "hemisphere", "topics": [ "hemisphere" ] }, { "page": "hemodynamicRF", "title": "Linear Model for FMRI Data", "topics": [ "hemodynamicRF" ] }, { "page": "hessianObjectness", "title": "hessianObjectness", "topics": [ "hessianObjectness" ] }, { "page": "hist.antsImage", "title": "Histogram of Values in an Image", "topics": [ "hist.antsImage" ] }, { "page": "histogramEqualizeImage", "title": "histogramEqualizeImage", "topics": [ "histogramEqualizeImage" ] }, { "page": "histogramMatchImage", "title": "histogramMatchImage", "topics": [ "histogramMatchImage" ] }, { "page": "histogramMatchImage2", "title": "Transform image intensities based on histogram mapping.", "topics": [ "histogramMatchImage2" ] }, { "page": "histogramWarpImageIntensities", "title": "Transform image intensities based on histogram mapping.", "topics": [ "histogramWarpImageIntensities" ] }, { "page": "humanize_anatomical_name", "title": "Humanize anatomical names by expanding abbreviations and reordering", "topics": [ "humanize_anatomical_name" ] }, { "page": "iBind", "title": "iBind", "topics": [ "iBind" ] }, { "page": "icawhiten", "title": "Simple icawhitening function.", "topics": [ "icawhiten" ] }, { "page": "ilr", "title": "Efficiently compute an image-based linear regression model (ilr)", "topics": [ "ilr" ] }, { "page": "ilr.predict", "title": "Predict from ilr output", "topics": [ "ilr.predict" ] }, { "page": "image2ClusterImages", "title": "Converts an image to several independent images.", "topics": [ "image2ClusterImages" ] }, { "page": "imageDomainToSpatialMatrix", "title": "Image domain to spatial position", "topics": [ "imageDomainToSpatialMatrix" ] }, { "page": "imageFileNames2ImageList", "title": "Simple imageFileNames2ImageListing function.", "topics": [ "imageFileNames2ImageList" ] }, { "page": "imageListToMatrix", "title": "Read Images into a Matrix", "topics": [ "imageListToMatrix" ] }, { "page": "imageSimilarity", "title": "imageSimilarity", "topics": [ "imageSimilarity" ] }, { "page": "imagesToMatrix", "title": "Read Images into a Matrix", "topics": [ "imagesToMatrix" ] }, { "page": "iMath", "title": "iMath", "topics": [ "iMath" ] }, { "page": "iMathOps", "title": "Operations for iMath Operator", "topics": [ "iMathOps" ] }, { "page": "indicator_opt_both_ways", "title": "Helper Function to Optimize Indicator Matrix with Best Sum", "topics": [ "indicator_opt_both_ways" ] }, { "page": "initializeEigenanatomy", "title": "Convert a matrix to a form that can be used to initialize sparse cca and pca.", "topics": [ "initializeEigenanatomy" ] }, { "page": "initializeSimlr", "title": "Initialize simlr", "topics": [ "initializeSimlr" ] }, { "page": "integrateVectorField", "title": "Integrate vector field", "topics": [ "integrateVectorField" ] }, { "page": "integrateVelocityField", "title": "integrateVelocityField", "topics": [ "integrateVelocityField" ] }, { "page": "interleaveMatrixWithItself", "title": "Simple interleaveMatrixWithItself function.", "topics": [ "interleaveMatrixWithItself" ] }, { "page": "interpret_simlr_vector", "title": "Interpret SiMLR Vector", "topics": [ "interpret_simlr_vector" ] }, { "page": "interpret_simlr_vector2", "title": "Interpret SiMLR Vector", "topics": [ "interpret_simlr_vector2" ] }, { "page": "inv_sqrt_sym", "title": "Inverse Square Root of a Symmetric Matrix", "topics": [ "inv_sqrt_sym" ] }, { "page": "inv_sqrt_sym_newton", "title": "Inverse square root of a symmetric matrix via Newton-Schulz", "topics": [ "inv_sqrt_sym_newton" ] }, { "page": "invariant_orthogonality_defect", "title": "Calculate the invariant orthogonality defect", "topics": [ "invariant_orthogonality_defect" ] }, { "page": "invertAntsrTransform", "title": "invertAntsrTransform", "topics": [ "invertAntsrTransform" ] }, { "page": "invertDisplacementField", "title": "invertDisplacementField", "topics": [ "invertDisplacementField" ] }, { "page": "is.antsImage", "title": "is.antsImage", "topics": [ "is.antsImage" ] }, { "page": "jhu_fa_labels", "title": "jhu_fa_labels", "topics": [ "jhu_fa_labels" ] }, { "page": "jhu_md_labels", "title": "jhu_md_labels", "topics": [ "jhu_md_labels" ] }, { "page": "jlfProp", "title": "Propagate Joint Label Fusion (JLF) solutions through a time series", "topics": [ "jlfProp" ] }, { "page": "joinEigenanatomy", "title": "Simple joinEigenanatomy function.", "topics": [ "joinEigenanatomy" ] }, { "page": "jointLabelFusion", "title": "joint label and intensity fusion", "topics": [ "jointLabelFusion" ] }, { "page": "jointSmoothMatrixReconstruction", "title": "joint smooth matrix prediction", "topics": [ "jointSmoothMatrixReconstruction" ] }, { "page": "kellyKapowski", "title": "Compute cortical thickness using the DiReCT algorithm.", "topics": [ "kellyKapowski" ] }, { "page": "kmeansSegmentation", "title": "k means image segmentation.", "topics": [ "kmeansSegmentation" ] }, { "page": "knnSmoothImage", "title": "k-nearest neighbors constrained image smoothing", "topics": [ "knnSmoothImage" ] }, { "page": "knnSmoothingMatrix", "title": "k-nearest neighbors constrained smoothing", "topics": [ "knnSmoothingMatrix" ] }, { "page": "l1_normalize_features", "title": "L1 Normalize Columns of a Matrix", "topics": [ "l1_normalize_features" ] }, { "page": "labelClusters", "title": "Simple labelClustering function.", "topics": [ "labelClusters" ] }, { "page": "labelGeometryMeasures", "title": "labelGeometryMeasures", "topics": [ "labelGeometryMeasures" ] }, { "page": "labelImageCentroids", "title": "labelImageCentroids", "topics": [ "labelImageCentroids" ] }, { "page": "labelImageRegistration", "title": "Perform label image registration.", "topics": [ "labelImageRegistration" ] }, { "page": "labelOverlapMeasures", "title": "labelOverlapMeasures", "topics": [ "labelOverlapMeasures" ] }, { "page": "labels2matrix", "title": "Convert label image to a matrix", "topics": [ "labels2matrix" ] }, { "page": "labelStats", "title": "labelStats", "topics": [ "labelStats" ] }, { "page": "lappend", "title": "Simple list append tool", "topics": [ "lappend" ] }, { "page": "list_simlr_optimizers", "title": "List Available SIMLR Optimizers", "topics": [ "list_simlr_optimizers" ] }, { "page": "load.ANTsR", "title": "Load R sessions with ANTsR objects", "topics": [ "load.ANTsR" ] }, { "page": "lobes", "title": "lobes", "topics": [ "lobes" ] }, { "page": "lobes_brainstem", "title": "lobes_brainstem", "topics": [ "lobes_brainstem" ] }, { "page": "localGyrificationIndex", "title": "Local gyrification index.", "topics": [ "localGyrificationIndex" ] }, { "page": "localJointLabelFusion", "title": "local joint label and intensity fusion", "topics": [ "localJointLabelFusion" ] }, { "page": "lowrankRowMatrix", "title": "Produces a low rank version of the input matrix", "topics": [ "lowrankRowMatrix" ] }, { "page": "make3ViewPNG", "title": "Rotate an existing 3d window into different views.", "topics": [ "make3ViewPNG" ] }, { "page": "makeGraph", "title": "Simple function to create and measure a graph from a square input matrix.", "topics": [ "makeGraph" ] }, { "page": "makeImage", "title": "Simple makeImage function.", "topics": [ "makeImage" ] }, { "page": "makePointsImage", "title": "Create label image from physical space points", "topics": [ "makePointsImage" ] }, { "page": "makePowersPointsImage", "title": "Label image from Powers points", "topics": [ "makePowersPointsImage" ] }, { "page": "mapAsymVar", "title": "Convert left/right variables to a measure of asymmetry", "topics": [ "mapAsymVar" ] }, { "page": "mapLRAverageVar", "title": "Convert left/right variables to an average measurement", "topics": [ "mapLRAverageVar" ] }, { "page": "mask_values", "title": "Simple Value extractor for antsImage Values", "topics": [ "mask_values" ] }, { "page": "maskImage", "title": "Mask input image by mask image.", "topics": [ "maskImage" ] }, { "page": "matrix2timeseries", "title": "Simple matrix2timeseries function.", "topics": [ "matrix2timeseries" ] }, { "page": "matrixToImages", "title": "Convert rows of a matrix to images", "topics": [ "matrixToImages" ] }, { "page": "MD_JHU_labels_edited", "title": "MD JHU labels edited", "topics": [ "MD_JHU_labels_edited" ] }, { "page": "mean", "title": "Mean for antsImage Objects", "topics": [ "mean.antsImage" ] }, { "page": "median", "title": "Median for antsImage Objects", "topics": [ "median.antsImage" ] }, { "page": "mergeChannels", "title": "merge images into a multiChannel antsImage", "topics": [ "mergeChannels" ] }, { "page": "mergeListToNDImage", "title": "mergeListToNDImage", "topics": [ "mergeListToNDImage" ] }, { "page": "mild", "title": "Efficiently compute a multivariate, image-based (mixed) linear decompositition (mild)", "topics": [ "mild" ] }, { "page": "milr", "title": "Efficiently compute a multivariate, penalized image-based linear regression model (milr)", "topics": [ "milr" ] }, { "page": "milr.predict", "title": "Predict from a milr output", "topics": [ "milr.predict" ] }, { "page": "mni2tal", "title": "Brett's mni2tal", "topics": [ "mni2tal" ] }, { "page": "morphology", "title": "Morphological image operations", "topics": [ "morphology" ] }, { "page": "mrvnrfs", "title": "multi-res voxelwise neighborhood random forest segmentation learning", "topics": [ "mrvnrfs" ] }, { "page": "mrvnrfs.predict", "title": "multi-res voxelwise neighborhood random forest segmentation", "topics": [ "mrvnrfs.predict" ] }, { "page": "mtl_description", "title": "mtl description", "topics": [ "mtl_description" ] }, { "page": "mtl_labels", "title": "mtl_labels", "topics": [ "mtl_labels" ] }, { "page": "multichannelPCA", "title": "Shape analysis of multichannel images based on PCA", "topics": [ "multichannelPCA" ] }, { "page": "multichannelToVector", "title": "Convert multichannel 'antsImage' to a vector.", "topics": [ "multichannelToVector" ] }, { "page": "multigrep", "title": "Grep entries with a vector search parameters", "topics": [ "multigrep" ] }, { "page": "multiLabelMorphology", "title": "Morphology on multi label images.", "topics": [ "multiLabelMorphology" ] }, { "page": "multiResRandomForestRegression", "title": "multiple resolution neighborhood random forest regression", "topics": [ "multiResRandomForestRegression" ] }, { "page": "multiscaleSVD", "title": "Multi-scale svd", "topics": [ "multiscaleSVD" ] }, { "page": "multiview_pca", "title": "Multiview PCA", "topics": [ "multiview_pca" ] }, { "page": "n3BiasFieldCorrection", "title": "N3 bias field correction", "topics": [ "n3BiasFieldCorrection" ] }, { "page": "n3BiasFieldCorrection2", "title": "N3 Bias field correction", "topics": [ "n3BiasFieldCorrection2" ] }, { "page": "n4BiasFieldCorrection", "title": "N4 bias field correction", "topics": [ "n4BiasFieldCorrection" ] }, { "page": "nbm3_labels", "title": "nbm3_labels", "topics": [ "nbm3_labels" ] }, { "page": "nbm3CH13", "title": "nbm3CH13", "topics": [ "nbm3CH13" ] }, { "page": "neg_violation", "title": "Nonnegativity Violation", "topics": [ "neg_violation" ] }, { "page": "networkEiganat", "title": "Convenience wrapper for eigenanatomy decomposition.", "topics": [ "networkEiganat" ] }, { "page": "NNHEmbed", "title": "Perform SiMLR Analysis on Multimodal ANTsPyMM Data", "topics": [ "NNHEmbed" ] }, { "page": "NNHEmbed_update_residuals", "title": "Update Residuals for SiMLR", "topics": [ "NNHEmbed_update_residuals" ] }, { "page": "nsa_flow", "title": "NSA-Flow Optimization", "topics": [ "nsa_flow" ] }, { "page": "nsa_flow_autograd", "title": "NSA-Flow Optimization via PyTorch AutoGrad (R wrapper)", "topics": [ "nsa_flow_autograd" ] }, { "page": "nsa_flow_fa_diagram", "title": "Generate NSA-Flow FA Flowchart Diagram", "topics": [ "nsa_flow_fa_diagram" ] }, { "page": "nsa_flow_flowchart", "title": "NSA-Flow Algorithm Flowchart", "topics": [ "nsa_flow_flowchart" ] }, { "page": "nsa_flow_pca", "title": "NSA-Flow Sparse PCA (stable + efficient)", "topics": [ "nsa_flow_pca" ] }, { "page": "nsa_flow_pca_fa", "title": "NSA-Flow Sparse PCA or FA", "topics": [ "nsa_flow_pca_fa" ] }, { "page": "nsa_flow_pca_fa_2", "title": "Perform Proximal Gradient Optimization for PCA or Factor Analysis", "topics": [ "nsa_flow_pca_fa_2" ] }, { "page": "nsa_flow_retract", "title": "Retraction onto the Stiefel Manifold", "topics": [ "nsa_flow_retract" ] }, { "page": "nsa_flow_retract_auto", "title": "Retraction onto the Stiefel Manifold (soft-polar multiplicative, with adaptive inv-sqrt)", "topics": [ "nsa_flow_retract_auto" ] }, { "page": "nsa_flow_torch", "title": "NSA-Flow Optimization via PyTorch", "topics": [ "nsa_flow_torch" ] }, { "page": "nsa_flow_torch_ag", "title": "NSA-Flow Optimization via PyTorch AutoGrad", "topics": [ "nsa_flow_torch_ag" ] }, { "page": "oneHotToSegmentation", "title": "Inverse one-hot transformation", "topics": [ "oneHotToSegmentation" ] }, { "page": "optimal_simlr_initializer", "title": "Calculate SiMLR energy for optimization Find Optimal SiMLR Initializer", "topics": [ "optimal_simlr_initializer" ] }, { "page": "optimize_indicator_matrix", "title": "Optimize Binary Indicator Matrix with Row Uniformity", "topics": [ "optimize_indicator_matrix" ] }, { "page": "orth_residual", "title": "Orthogonality Residual", "topics": [ "orth_residual" ] }, { "page": "orthogonalize_feature_space", "title": "Orthogonalize a List of Matrices via Gradient Descent with Convergence Check", "topics": [ "orthogonalize_feature_space" ] }, { "page": "orthogonalizeAndQSparsify", "title": "Sparsify and optionally orthogonalize a matrix", "topics": [ "orthogonalizeAndQSparsify" ] }, { "page": "orthogonalizeAndQSparsifyOld", "title": "sparsify a matrix", "topics": [ "orthogonalizeAndQSparsifyOld" ] }, { "page": "padImageByFactor", "title": "Pad an image based on a factor.", "topics": [ "padImageByFactor" ] }, { "page": "padOrCropImageToSize", "title": "Pad or crop image to a specified size", "topics": [ "padOrCropImageToSize" ] }, { "page": "pairwise_matrix_similarity", "title": "pairwise application of matrix similarity to matrix List projected onto a feature list", "topics": [ "pairwise_matrix_similarity" ] }, { "page": "pairwiseImageDistanceMatrix", "title": "Simple pairwiseImageDistanceMatrix function for images", "topics": [ "pairwiseImageDistanceMatrix" ] }, { "page": "partialVolumeCorrection", "title": "Perform partial volume correction for ASL images.", "topics": [ "partialVolumeCorrection" ] }, { "page": "perfusionregression", "title": "Perfusion Regression", "topics": [ "perfusionregression" ] }, { "page": "petSUVR", "title": "Compute SUVR from PET time series images", "topics": [ "petSUVR" ] }, { "page": "accessor-methods", "title": "Extract Image Attributes 'pixeltype' from antsImages", "topics": [ "components", "components,antsImage-method", "components<-", "components<-,antsImage-method", "direction", "direction,antsImage-method", "direction<-", "direction<-,antsImage-method", "origin", "origin,antsImage-method", "origin<-", "origin<-,antsImage-method", "pixeltype", "pixeltype,antsImage-method", "pixeltype<-", "pixeltype<-,antsImage-method", "spacing", "spacing,antsImage-method", "spacing<-", "spacing<-,antsImage-method" ] }, { "page": "plot_energy_decomposition", "title": "Plot Energy Decomposition During SIMLR Optimization", "topics": [ "plot_energy_decomposition" ] }, { "page": "plot_features", "title": "Plot Features", "topics": [ "plot_features" ] }, { "page": "plot.antsImage", "title": "Plotting an image slice or multi-slice with optional color overlay.", "topics": [ "plot.antsImage" ] }, { "page": "plotBasicNetwork", "title": "Simple plotBasicNetwork function.", "topics": [ "plotBasicNetwork" ] }, { "page": "plotPrettyGraph", "title": "Simple plotPrettyGraph function saves to png.", "topics": [ "plotPrettyGraph" ] }, { "page": "posthoc_fa_summary", "title": "Post-hoc Factor Analysis Summary: Scores, Communalities, and Variance Explained", "topics": [ "posthoc_fa_summary" ] }, { "page": "powers_areal_mni_itk", "title": "powers_areal_mni_itk", "topics": [ "powers_areal_mni_itk" ] }, { "page": "powers_mni_itk", "title": "powers mni itk", "topics": [ "powers_mni_itk" ] }, { "page": "ppmi_template_500Parcels_Yeo2011_17Networks_2023_homotopic", "title": "ppmi template 500Parcels Yeo2011 17Networks 2023 homotopic", "topics": [ "ppmi_template_500Parcels_Yeo2011_17Networks_2023_homotopic" ] }, { "page": "ppmi_yeo_labels", "title": "ppmi_yeo_labels", "topics": [ "ppmi_yeo_labels" ] }, { "page": "predict.fusedRidge", "title": "Predict Method for Fused Ridge Regression", "topics": [ "predict.fusedRidge" ] }, { "page": "predict.fusedRidgeDirect", "title": "Predict Method for Direct Fused Ridge Regression", "topics": [ "predict.fusedRidgeDirect" ] }, { "page": "predict.fusedRidgeTorch", "title": "Predict Method for PyTorch Fused Ridge Regression", "topics": [ "predict.fusedRidgeTorch" ] }, { "page": "predictSimlr", "title": "predict output matrices from simlr solution", "topics": [ "predictSimlr" ] }, { "page": "preprocessfMRI", "title": "Preprocess BOLD fMRI image data.", "topics": [ "preprocessfMRI" ] }, { "page": "preprocessRestingBOLD", "title": "Preprocess resting BOLD fMRI image data.", "topics": [ "preprocessRestingBOLD" ] }, { "page": "priorBasedSegmentation", "title": "spatial prior-based image segmentation.", "topics": [ "priorBasedSegmentation" ] }, { "page": "project_to_orthonormal_nonnegative", "title": "Project Non-Negative Matrix to Orthonormal Columns Matrix", "topics": [ "project_to_orthonormal_nonnegative" ] }, { "page": "project_to_partially_orthonormal_nonnegative", "title": "Project Non-Negative Matrix with Controllable Orthonormality", "topics": [ "project_to_partially_orthonormal_nonnegative" ] }, { "page": "quantifyCBF", "title": "quantifyCBF", "topics": [ "quantifyCBF" ] }, { "page": "quantifySNPs", "title": "Simple quantifySNPs function.", "topics": [ "quantifySNPs" ] }, { "page": "quantile.antsImage", "title": "Sample Quantiles", "topics": [ "quantile.antsImage" ] }, { "page": "randcca", "title": "randomized cca function.", "topics": [ "randcca" ] }, { "page": "randomlyTransformImageData", "title": "Randomly transform image data (optional: with corresponding segmentations).", "topics": [ "randomlyTransformImageData" ] }, { "page": "randomMask", "title": "Get a random mask", "topics": [ "randomMask" ] }, { "page": "randsvd", "title": "randomized svd function.", "topics": [ "randsvd" ] }, { "page": "randwhiten", "title": "randomized whitening function.", "topics": [ "randwhiten" ] }, { "page": "rankBasedMatrixSegmentation", "title": "rank-based segmentation of a matrix", "topics": [ "rankBasedMatrixSegmentation" ] }, { "page": "rankIntensity", "title": "rank intensity transformation for an image", "topics": [ "rankIntensity" ] }, { "page": "rapidlyInspectImageData", "title": "Simple rapidlyInspectImageData function.", "topics": [ "rapidlyInspectImageData" ] }, { "page": "read_simlr", "title": "Read all SiMLR outputs from disk", "topics": [ "read_simlr" ] }, { "page": "read_simlr_data_frames", "title": "Read a list of data frames from disk with SiMLR-specific naming convention", "topics": [ "read_simlr_data_frames" ] }, { "page": "readAntsrTransform", "title": "readAntsrTransform", "topics": [ "readAntsrTransform" ] }, { "page": "readNormalizedPopulationData", "title": "Read normalized population from h5 file or directory", "topics": [ "readNormalizedPopulationData" ] }, { "page": "reconstructImageFromPatches", "title": "Reconstruct image from a list of patches.", "topics": [ "reconstructImageFromPatches" ] }, { "page": "refbasis_brain", "title": "refbasis brain", "topics": [ "refbasis_brain" ] }, { "page": "refbasis_head", "title": "refbasis head", "topics": [ "refbasis_head" ] }, { "page": "reference_basis", "title": "reference basis", "topics": [ "reference_basis" ] }, { "page": "reflectImage", "title": "reflectImage", "topics": [ "reflectImage" ] }, { "page": "reflectionMatrix", "title": "reflectionMatrix", "topics": [ "reflectionMatrix" ] }, { "page": "regressionMatchImage", "title": "Image intensity normalization using linear regression.", "topics": [ "regressionMatchImage" ] }, { "page": "regressProjections", "title": "Regression on image set projection", "topics": [ "regressProjections" ] }, { "page": "regularizeSimlr", "title": "Automatically produce regularization matrices for simlr", "topics": [ "regularizeSimlr" ] }, { "page": "reho", "title": "REHO", "topics": [ "reho" ] }, { "page": "renormalizeProbabilityImages", "title": "Normalize (modified) probability images", "topics": [ "renormalizeProbabilityImages" ] }, { "page": "reorientImage", "title": "reorient image by its principal axis", "topics": [ "reorientImage" ] }, { "page": "resampleImage", "title": "resampleImage", "topics": [ "resampleImage" ] }, { "page": "resampleImageToTarget", "title": "resampleImageToTarget", "topics": [ "resampleImageToTarget" ] }, { "page": "resels", "title": "Estimates image resels", "topics": [ "resels" ] }, { "page": "reset_optimizer_state", "title": "Reset Optimizer State", "topics": [ "reset_optimizer_state" ] }, { "page": "rfSegmentation", "title": "A rfSegmentation function.", "topics": [ "rfSegmentation" ] }, { "page": "rfSegmentationPredict", "title": "A rfSegmentationPredict function.", "topics": [ "rfSegmentationPredict" ] }, { "page": "rftPval", "title": "RFT p-values", "topics": [ "rftPval" ] }, { "page": "rftResults", "title": "RFT Statistical Results", "topics": [ "rftResults" ] }, { "page": "ri", "title": "Minimal function for creating r images", "topics": [ "ri" ] }, { "page": "ripmmarc", "title": "Rotation Invariant Patch-based Multi-Modality Analysis aRChitecture", "topics": [ "ripmmarc" ] }, { "page": "ripmmarcBasisImage", "title": "Generate an antsImage from ripmmarc basis data", "topics": [ "ripmmarcBasisImage" ] }, { "page": "ripmmarcPop", "title": "RIPMMARC population basis", "topics": [ "ripmmarcPop" ] }, { "page": "robustMatrixTransform", "title": "Simple robustMatrixTransform function.", "topics": [ "robustMatrixTransform" ] }, { "page": "rsfDenoise", "title": "WIP: data-driven denoising for resting state fMRI", "topics": [ "rsfDenoise" ] }, { "page": "rvcoef", "title": "Computes the RV-Coefficient (Optimized Public API)", "topics": [ "rvcoef" ] }, { "page": "rvcoef_components", "title": "Computes the RV-Coefficient (Internal)", "topics": [ "rvcoef_components" ] }, { "page": "rvcoef_gram_impl", "title": "Computes the RV-Coefficient (Internal) Gram Matrix Method for Tall data", "topics": [ "rvcoef_gram_impl" ] }, { "page": "rvcoef_trace_impl", "title": "Computes the RV-Coefficient (Internal) Trace Method for Wide data", "topics": [ "rvcoef_trace_impl" ] }, { "page": "safe_pca", "title": "Safe PCA with Deterministic Bad-Column Repair", "topics": [ "safe_pca" ] }, { "page": "save.ANTsR", "title": "Save R sessions including ANTsR objects", "topics": [ "save.ANTsR" ] }, { "page": "scaleSpaceFeatureDetection", "title": "Scale space feature detector", "topics": [ "scaleSpaceFeatureDetection" ] }, { "page": "sd", "title": "SD generic", "topics": [ "sd", "sd.antsImage", "sd.default" ] }, { "page": "segmentationRefinement.predict", "title": "Segmentation refinement using corrective learning (prediction)", "topics": [ "segmentationRefinement.predict" ] }, { "page": "segmentationRefinement.train", "title": "Segmentation refinement using corrective learning (training)", "topics": [ "segmentationRefinement.train" ] }, { "page": "segmentationToOneHot", "title": "One-hot encoding function", "topics": [ "segmentationToOneHot" ] }, { "page": "segmentShapeFromImage", "title": "convolution-based shape identification", "topics": [ "segmentShapeFromImage" ] }, { "page": "select_joint_k", "title": "Select an Optimal Joint Number of Components for Multi-View Data", "topics": [ "select_joint_k" ] }, { "page": "setANTsDeterministic", "title": "Set ANTs deterministic behavior", "topics": [ "setANTsDeterministic" ] }, { "page": "setAntsrTransformFixedParameters", "title": "setAntsrTransformFixedParameters", "topics": [ "setAntsrTransformFixedParameters" ] }, { "page": "setAntsrTransformParameters", "title": "setAntsrTransformParameters", "topics": [ "setAntsrTransformParameters" ] }, { "page": "setSeedBasedOnTime", "title": "Set Seed Based on Current Time", "topics": [ "setSeedBasedOnTime" ] }, { "page": "shorten_pymm_names", "title": "shorter antspymm names", "topics": [ "shorten_pymm_names" ] }, { "page": "simlr", "title": "Similarity-driven multiview linear reconstruction model (simlr) for N modalities", "topics": [ "simlr" ] }, { "page": "simlr_feature_orth", "title": "Compute the Average Invariant Orthogonality Defect for Multiple Features", "topics": [ "simlr_feature_orth" ] }, { "page": "simlr_impute", "title": "Impute missing SiMLR data in a specified column based on other columns", "topics": [ "simlr_impute" ] }, { "page": "simlr_path_models", "title": "SiMLR Path Models helper", "topics": [ "simlr_path_models" ] }, { "page": "simlr_sparseness", "title": "Apply SIMLR Sparseness and Normalize Features", "topics": [ "simlr_sparseness" ] }, { "page": "simlr.parameters", "title": "Generate Parameter Grid for SIMLR Search", "topics": [ "simlr.parameters" ] }, { "page": "simlr.perm", "title": "Assess Significance of SiMLR Call", "topics": [ "simlr.perm" ] }, { "page": "simlr.search", "title": "Perform Parallel SIMLR Grid Search (with Progress Bar)", "topics": [ "simlr.search" ] }, { "page": "simlrU", "title": "Compute the low-dimensional u matrix for simlr", "topics": [ "simlrU" ] }, { "page": "simulateBiasField", "title": "Simulate random bias field", "topics": [ "simulateBiasField" ] }, { "page": "simulateDisplacementField", "title": "simulateDisplacementField", "topics": [ "simulateDisplacementField" ] }, { "page": "skeletonize", "title": "Skeletonize a binary segmentation.", "topics": [ "skeletonize" ] }, { "page": "smoothAppGradCCA", "title": "cca via sparse smooth matrix prediction", "topics": [ "smoothAppGradCCA" ] }, { "page": "smoothImage", "title": "Smooth image", "topics": [ "smoothImage" ] }, { "page": "smoothMatrixPrediction", "title": "smooth matrix prediction", "topics": [ "smoothMatrixPrediction" ] }, { "page": "smoothMultiRegression", "title": "Reconstruct a n by k vector given n by p matrix of predictors.", "topics": [ "smoothMultiRegression" ] }, { "page": "smoothRegression", "title": "smooth matrix-based regression", "topics": [ "smoothRegression" ] }, { "page": "softwareVersions", "title": "softwareVersions", "topics": [ "softwareVersions" ] }, { "page": "sparseDecom", "title": "Convenience wrapper for eigenanatomy decomposition.", "topics": [ "sparseDecom" ] }, { "page": "sparseDecom2", "title": "Convenience wrapper for 2-view eigenanatomy decomposition.", "topics": [ "sparseDecom2" ] }, { "page": "sparseDecom2boot", "title": "Convenience wrapper for 2-view eigenanatomy decomposition w/bootstrap initialization.", "topics": [ "sparseDecom2boot" ] }, { "page": "sparseDecomboot", "title": "Convenience wrapper for eigenanatomy decomposition.", "topics": [ "sparseDecomboot" ] }, { "page": "sparseDistanceMatrix", "title": "Create sparse distance, covariance or correlation matrix", "topics": [ "sparseDistanceMatrix" ] }, { "page": "sparseDistanceMatrixXY", "title": "Create sparse distance, covariance or correlation matrix from x, y", "topics": [ "sparseDistanceMatrixXY" ] }, { "page": "sparseRegression", "title": "Sparse regression on input images.", "topics": [ "sparseRegression" ] }, { "page": "sparsify_by_column_winner", "title": "Sparsify a Matrix via Column-wise Winner-Take-All", "topics": [ "sparsify_by_column_winner" ] }, { "page": "spatialbayesianlm", "title": "spatially constrained bayesian regression function.", "topics": [ "spatialbayesianlm" ] }, { "page": "splitChannels", "title": "split a multichannel antsImage", "topics": [ "splitChannels" ] }, { "page": "splitData", "title": "Split data for testing and training", "topics": [ "splitData" ] }, { "page": "splitMask", "title": "split a mask into n labeled sub-masks", "topics": [ "splitMask" ] }, { "page": "splitNDImageToList", "title": "splitNDImageToList", "topics": [ "splitNDImageToList" ] }, { "page": "statFieldThresh", "title": "Produces a threshold value based on cluster or voxel level statistics", "topics": [ "statFieldThresh" ] }, { "page": "step", "title": "Take One Optimization Step", "topics": [ "step" ] }, { "page": "subgradientL1Regression", "title": "Simple subgradientL1Regression function.", "topics": [ "subgradientL1Regression" ] }, { "page": "subjectDataToGroupDataFrame", "title": "convert subject matrix data to a row in a dataframe.", "topics": [ "subjectDataToGroupDataFrame" ] }, { "page": "subset", "title": "Subsetting antsImage Objects", "topics": [ "subset.antsImage" ] }, { "page": "sum_preserving_matrix_partition", "title": "Sum preserving matrix partition", "topics": [ "sum_preserving_matrix_partition" ] }, { "page": "symm", "title": "Symmetrize a Matrix", "topics": [ "symm" ] }, { "page": "T_template0_LobesBstem", "title": "T template0 LobesBstem", "topics": [ "T_template0_LobesBstem" ] }, { "page": "take_abs_unsigned", "title": "Take Absolute Value of Unsigned Columns", "topics": [ "take_abs_unsigned" ] }, { "page": "taskFMRI", "title": "Simple taskFMRI function.", "topics": [ "taskFMRI" ] }, { "page": "temporalwhiten", "title": "Simple autocorrelation-based temporal whitening function.", "topics": [ "temporalwhiten" ] }, { "page": "testEanat", "title": "Test eigenanatomy in order", "topics": [ "testEanat" ] }, { "page": "thresholdImage", "title": "Threshold Image", "topics": [ "thresholdImage" ] }, { "page": "timeseries2matrix", "title": "Time-series image to matrix", "topics": [ "timeseries2matrix" ] }, { "page": "timeseriesN3", "title": "Run N3 on slices of timeseries.", "topics": [ "timeseriesN3" ] }, { "page": "timeserieswindow2matrix", "title": "Time-series image to matrix of time windows around user-specified events", "topics": [ "timeserieswindow2matrix" ] }, { "page": "tissues", "title": "tissues", "topics": [ "tissues" ] }, { "page": "tracts", "title": "tracts", "topics": [ "tracts" ] }, { "page": "transform_matrix", "title": "Transform a matrix by standard preprocessing", "topics": [ "transform_matrix" ] }, { "page": "transform_prior_rows_to_uncorrelated", "title": "Transform prior rows to (approximately) uncorrelated representative rows", "topics": [ "transform_prior_rows_to_uncorrelated" ] }, { "page": "trapz", "title": "Calculate the area under a sampled curve (or set of curves).", "topics": [ "trapz" ] }, { "page": "undo_transform_matrix", "title": "Undo a previously applied matrix transform", "topics": [ "undo_transform_matrix" ] }, { "page": "unique", "title": "Unique for antsImage Objects", "topics": [ "unique.antsImage" ] }, { "page": "usePkg", "title": "Use any package. 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