Source code for nighres.laminar.volumetric_layering

import sys
import os
import numpy as np
import nibabel as nb
import nighresjava
from import load_volume, save_volume
from ..utils import _output_dir_4saving, _fname_4saving, \
                    _check_topology_lut_dir, _check_available_memory

[docs]def volumetric_layering(inner_levelset, outer_levelset, n_layers=4, topology_lut_dir=None, method="volume-preserving", layer_dir="outward", curv_scale=3, save_data=False, overwrite=False, output_dir=None, file_name=None): '''Equivolumetric layering of the cortical sheet. Parameters ---------- inner_levelset: niimg Levelset representation of the inner surface, typically GM/WM surface outer_levelset: niimg Levelset representation of the outer surface, typically GM/CSF surface n_layers : int, optional Number of layers to be created (default is 10) topology_lut_dir: str, optional Path to directory in which topology files are stored (default is stored in TOPOLOGY_LUT_DIR) method: str Which model to use, either "volume-preserving" or "distance-preserving" (default is "volume-preserving") layer_dir: str Direction to perform the layering, either "outward" or "inward" (default is "outward") curv_scale: int Scale of the curvature approximation window in voxels (default is 3, computation may become very slow for higher values) save_data: bool Save output data to file (default is False) overwrite: bool Overwrite existing results (default is False) output_dir: str, optional Path to desired output directory, will be created if it doesn't exist file_name: str, optional Desired base name for output files with file extension (suffixes will be added) Returns ---------- dict Dictionary collecting outputs under the following keys (suffix of output files in brackets) * depth (niimg): Continuous depth from 0 (inner surface) to 1 (outer surface) (_layering-depth) * layers (niimg): Discrete layers from 1 (bordering inner surface) to n_layers (bordering outer surface) (_layering-layers) * boundaries (niimg): Levelset representations of boundaries between all layers in 4D (_layering-boundaries) Notes ---------- Original Java module by Miriam Waehnert, Pierre-Louis Bazin and Juliane Dinse. Algorithm details can be found in [1]_ References ---------- .. [1] Waehnert et al (2014) Anatomically motivated modeling of cortical laminae. DOI: 10.1016/j.neuroimage.2013.03.078 ''' print('\nVolumetric Layering') # check topology lut dir and set default if not given topology_lut_dir = _check_topology_lut_dir(topology_lut_dir) # make sure that saving related parameters are correct if save_data: output_dir = _output_dir_4saving(output_dir, inner_levelset) depth_file = os.path.join(output_dir, _fname_4saving(module=__name__,file_name=file_name, rootfile=inner_levelset, suffix='layering-depth')) layer_file = os.path.join(output_dir, _fname_4saving(module=__name__,file_name=file_name, rootfile=inner_levelset, suffix='layering-layers')) boundary_file = os.path.join(output_dir, _fname_4saving(module=__name__,file_name=file_name, rootfile=inner_levelset, suffix='layering-boundaries')) if overwrite is False \ and os.path.isfile(depth_file) \ and os.path.isfile(layer_file) \ and os.path.isfile(boundary_file) : print("skip computation (use existing results)") output = {'depth': depth_file, 'layers': layer_file, 'boundaries': boundary_file} return output # start virutal machine if not already running try: mem = _check_available_memory() nighresjava.initVM(initialheap=mem['init'], maxheap=mem['max']) except ValueError: pass # initate class lamination = nighresjava.LaminarVolumetricLayering() # load the data inner_img = load_volume(inner_levelset) inner_data = inner_img.get_data() hdr = inner_img.header aff = inner_img.affine resolution = [x.item() for x in hdr.get_zooms()] dimensions = inner_data.shape outer_data = load_volume(outer_levelset).get_data() # set parameters from input images lamination.setDimensions(dimensions[0], dimensions[1], dimensions[2]) lamination.setResolutions(resolution[0], resolution[1], resolution[2]) lamination.setInnerDistanceImage(nighresjava.JArray('float')( (inner_data.flatten('F')).astype(float))) lamination.setOuterDistanceImage(nighresjava.JArray('float')( (outer_data.flatten('F')).astype(float))) lamination.setNumberOfLayers(n_layers) lamination.setTopologyLUTdirectory(topology_lut_dir) # advanced parameters lamination.setLayeringDirection(layer_dir) lamination.setLayeringMethod(method) lamination.setCurvatureApproximationScale(curv_scale) # execute class try: lamination.execute() except: # if the Java module fails, reraise the error it throws print("\n The underlying Java code did not execute cleanly: ") print(sys.exc_info()[0]) raise return # collect data depth_data = np.reshape(np.array(lamination.getContinuousDepthMeasurement(), dtype=np.float32), dimensions, 'F') hdr['cal_max'] = np.nanmax(depth_data) depth = nb.Nifti1Image(depth_data, aff, hdr) layer_data = np.reshape(np.array(lamination.getDiscreteSampledLayers(), dtype=np.int32), dimensions, 'F') hdr['cal_max'] = np.nanmax(layer_data) layers = nb.Nifti1Image(layer_data, aff, hdr) boundary_len = lamination.getLayerBoundarySurfacesLength() boundary_data = np.reshape(np.array(lamination.getLayerBoundarySurfaces(), dtype=np.float32), (dimensions[0], dimensions[1], dimensions[2], boundary_len), 'F') hdr['cal_min'] = np.nanmin(boundary_data) hdr['cal_max'] = np.nanmax(boundary_data) boundaries = nb.Nifti1Image(boundary_data, aff, hdr) if save_data: save_volume(depth_file, depth) save_volume(layer_file, layers) save_volume(boundary_file, boundaries) return {'depth': depth_file, 'layers': layer_file, 'boundaries': boundary_file} else: return {'depth': depth, 'layers': layers, 'boundaries': boundaries}