## ----echo = FALSE, message = FALSE-------------------------------------------- knitr::opts_chunk$set(collapse = TRUE, comment = "#>") library(neuroim2) ## ----------------------------------------------------------------------------- set.seed(1) demo_path <- system.file("extdata", "global_mask_v4.nii", package = "neuroim2") vol3d <- read_vol(demo_path) # 3D volume vec4d <- read_vec(demo_path) # 4D NeuroVec (same file) sp3 <- space(vol3d) dims <- dim(vol3d) ## ----------------------------------------------------------------------------- blur_light <- gaussian_blur(vol3d, vol3d, sigma = 2, window = 1) blur_strong <- gaussian_blur(vol3d, vol3d, sigma = 4, window = 2) dim(blur_light) ## ----------------------------------------------------------------------------- gf_vol <- guided_filter(vol3d, radius = 4, epsilon = 0.7^2) gf_vol ## ----------------------------------------------------------------------------- bf_vol <- bilateral_filter( vol3d, spatial_sigma = 2, intensity_sigma = 1, window = 1 ) bf_vol ## ----------------------------------------------------------------------------- sharp_vol <- laplace_enhance(vol3d, k = 2, patch_size = 3, search_radius = 2, h = 0.7) sharp_vol ## ----------------------------------------------------------------------------- mask3d <- read_vol(system.file("extdata", "global_mask_v4.nii", package = "neuroim2")) bf4d <- bilateral_filter_4d( vec4d, mask3d, spatial_sigma = 2, intensity_sigma = 1, temporal_sigma = 1, spatial_window = 1, temporal_window = 1, temporal_spacing = 1 ) dim(bf4d) ## ----------------------------------------------------------------------------- cgf <- cgb_filter( vec4d, mask = mask3d, spatial_sigma = 3, window = NULL, # auto from spatial_sigma and spacing corr_map = "power", corr_param = 2, topk = 16, passes = 1, lambda = 1 ) dim(cgf) ## ----------------------------------------------------------------------------- cg_out <- cgb_filter(vec4d, mask3d, spatial_sigma = 3, window = NULL, topk = 16, return_graph = TRUE) str(cg_out$graph)