import os
import sys
import numpy as np
import nibabel as nb
import nighresjava
from ..io import load_volume, save_volume, load_mesh_geometry, save_mesh_geometry
from ..utils import _output_dir_4saving, _fname_4saving,_check_available_memory
[docs]def levelset_to_mesh(levelset_image, connectivity="18/6", level=0.0,
inclusive=True, save_data=False, overwrite=False,
output_dir=None, file_name=None):
"""Levelset to mesh
Creates a triangulated mesh from the distance to a levelset surface
representation using a connectivity-consistent marching cube algorithm.
Parameters
----------
levelset_image: niimg
Levelset image to be turned into a mesh
connectivity: {"6/18","6/26","18/6","26/6"}, optional
Choice of digital connectivity to build the mesh (default is 18/6)
level: float, optional
Value of the levelset function to use as isosurface (default is 0)
inclusive: bool, optional
Whether voxels at the exact 'level' value are inside the isosurface
(default is True)
save_data: bool, optional
Save output data to file (default is False)
overwrite: bool, optional
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)
* result (mesh): Surface mesh dictionary of "points" and "faces"
(_l2m-mesh)
Notes
----------
Ported from original Java module by Pierre-Louis Bazin. Original algorithm
from [1]_ and adapted from [2]_.
References
----------
.. [1] Han et al (2003). A Topology Preserving Level Set Method for
Geometric Deformable Models
doi:
.. [2] Lucas et al (2010). The Java Image Science Toolkit (JIST) for
Rapid Prototyping and Publishing of Neuroimaging Software
doi:
"""
print("\nLevelset to Mesh")
# make sure that saving related parameters are correct
if save_data:
output_dir = _output_dir_4saving(output_dir, levelset_image)
mesh_file = os.path.join(output_dir,
_fname_4saving(module=__name__,file_name=file_name,
rootfile=levelset_image,
suffix='l2m-mesh',ext="vtk"))
if overwrite is False \
and os.path.isfile(mesh_file) :
print("skip computation (use existing results)")
output = {'result': mesh_file}
return output
# start virtual machine if not running
try:
mem = _check_available_memory()
nighresjava.initVM(initialheap=mem['init'], maxheap=mem['max'])
except ValueError:
pass
# initiate class
algorithm = nighresjava.SurfaceLevelsetToMesh()
# load the data
lvl_img = load_volume(levelset_image)
lvl_data = lvl_img.get_data()
hdr = lvl_img.header
aff = lvl_img.affine
resolution = [x.item() for x in hdr.get_zooms()]
dimensions = lvl_data.shape
algorithm.setResolutions(resolution[0], resolution[1], resolution[2])
algorithm.setDimensions(dimensions[0], dimensions[1], dimensions[2])
algorithm.setLevelsetImage(nighresjava.JArray('float')(
(lvl_data.flatten('F')).astype(float)))
algorithm.setConnectivity(connectivity)
algorithm.setZeroLevel(level)
algorithm.setInclusive(inclusive)
# execute class
try:
algorithm.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 outputs
npt = int(np.array(algorithm.getPointList(), dtype=np.float32).shape[0]/3)
mesh_points = np.reshape(np.array(algorithm.getPointList(),
dtype=np.float32), (npt,3), 'C')
nfc = int(np.array(algorithm.getTriangleList(), dtype=np.int32).shape[0]/3)
mesh_faces = np.reshape(np.array(algorithm.getTriangleList(),
dtype=np.int32), (nfc,3), 'C')
# create the mesh dictionary
mesh = {"points": mesh_points, "faces": mesh_faces}
if save_data:
save_mesh_geometry(mesh_file, mesh)
return {'result': mesh_file}
else:
return {'result': mesh}