def plot_3d_surface(self,
roi,
channel,
segment=False,
flipz=False,
offset=None):
"""Plots areas with greater intensity as 3D surfaces.
The scene will be cleared before display.
Args:
roi (:class:`numpy.ndarray`): Region of interest either as a 3D
``z,y,x`` or 4D ``z,y,x,c`` array.
channel (int): Channel to select, which can be None to indicate all
channels.
segment (bool): True to denoise and segment ``roi`` before
displaying, which may remove artifacts that might otherwise
lead to spurious surfaces. Defaults to False.
flipz: True to invert ``roi`` along z-axis to match handedness
of Matplotlib with z progressing upward; defaults to False.
offset (Sequence[int]): Origin coordinates in ``z,y,x``; defaults
to None.
Returns:
list: List of Mayavi surfaces for each displayed channel, which
are also stored in :attr:`surfaces`.
"""
# Plot in Mayavi
print("viewing 3D surface")
pipeline = self.scene.mlab.pipeline
settings = config.roi_profile
if flipz:
# invert along z-axis to match handedness of Matplotlib with z up
roi = roi[::-1]
if offset is not None:
# invert z-offset and translate by ROI z-size so ROI is
# mirrored across the xy-plane
offset = np.copy(offset)
offset[0] = -offset[0] - roi.shape[0]
isotropic = plot_3d.get_isotropic_vis(settings)
# saturate to remove noise and normalize values
roi = plot_3d.saturate_roi(roi, channel=channel)
# turn off segmentation if ROI too big (arbitrarily set here as
# > 10 million pixels) to avoid performance hit and since likely showing
# large region of downsampled image anyway, where don't need hi res
num_pixels = np.prod(roi.shape)
to_segment = num_pixels < 10000000
time_start = time()
multichannel, channels = plot_3d.setup_channels(roi, channel, 3)
surfaces = []
for chl in channels:
roi_show = roi[..., chl] if multichannel else roi
# clip to minimize sub-nuclear variation
roi_show = np.clip(roi_show, 0.2, 0.8)
if segment:
# denoising makes for much cleaner images but also seems to
# allow structures to blend together
# TODO: consider segmenting individual structures and rendering
# as separate surfaces to avoid blending
roi_show = restoration.denoise_tv_chambolle(roi_show,
weight=0.1)
# build surface from segmented ROI
if to_segment:
vmin, vmax = np.percentile(roi_show, (40, 70))
walker = segmenter.segment_rw(roi_show,
chl,
vmin=vmin,
vmax=vmax)
roi_show *= np.subtract(walker[0], 1)
else:
print("deferring segmentation as {} px is above threshold".
format(num_pixels))
# ROI is in (z, y, x) order, so need to transpose or swap x,z axes
roi_show = np.transpose(roi_show)
surface = pipeline.scalar_field(roi_show)
# Contour -> Surface pipeline
# create the surface
surface = pipeline.contour(surface)
# remove many more extraneous points
surface = pipeline.user_defined(surface,
filter="SmoothPolyDataFilter")
surface.filter.number_of_iterations = 400
surface.filter.relaxation_factor = 0.015
# distinguishing pos vs neg curvatures?
surface = pipeline.user_defined(surface, filter="Curvatures")
surface = self.scene.mlab.pipeline.surface(surface)
module_manager = surface.module_manager
module_manager.scalar_lut_manager.data_range = np.array([-2, 0])
module_manager.scalar_lut_manager.lut_mode = "gray"
'''
# Surface pipleline with contours enabled (similar to above?)
surface = pipeline.contour_surface(
surface, color=(0.7, 1, 0.7), line_width=6.0)
surface.actor.property.representation = 'wireframe'
#surface.actor.property.line_width = 6.0
surface.actor.mapper.scalar_visibility = False
'''
'''
# IsoSurface pipeline
# uses unique IsoSurface module but appears to have
# similar output to contour_surface
surface = pipeline.iso_surface(surface)
# limit contours for simpler surfaces including smaller file sizes;
# TODO: consider making settable as arg or through profile
surface.contour.number_of_contours = 1
try:
# increase min to further reduce complexity
surface.contour.minimum_contour = 0.5
surface.contour.maximum_contour = 0.8
except Exception as e:
print(e)
print("ignoring min/max contour for now")
'''
if offset is not None:
# translate to offset scaled by isotropic factor
surface.actor.actor.position = np.multiply(offset,
isotropic)[::-1]
# scale surfaces, which expands/contracts but does not appear
# to translate the surface position
surface.actor.actor.scale = isotropic[::-1]
surfaces.append(surface)
# keep visual ordering of surfaces when opacity is reduced
self.scene.renderer.use_depth_peeling = True
print("time to render 3D surface: {}".format(time() - time_start))
self.surfaces = surfaces
return surfaces
def threshold(roi):
"""Thresholds the ROI, with options for various techniques as well as
post-thresholding morphological filtering.
Args:
roi: Region of interest, given as [z, y, x].
Returns:
The thresholded region.
"""
settings = config.roi_profile
thresh_type = settings["thresholding"]
size = settings["thresholding_size"]
thresholded = roi
roi_thresh = 0
# various thresholding model
if thresh_type == "otsu":
try:
roi_thresh = filters.threshold_otsu(roi, size)
thresholded = roi > roi_thresh
except ValueError as e:
# np.histogram may give an error apparently if any NaN, so
# workaround is set all elements in ROI to False
print(e)
thresholded = roi > np.max(roi)
elif thresh_type == "local":
roi_thresh = np.copy(roi)
for i in range(roi_thresh.shape[0]):
roi_thresh[i] = filters.threshold_local(roi_thresh[i],
size,
mode="wrap")
thresholded = roi > roi_thresh
elif thresh_type == "local-otsu":
# TODO: not working yet
selem = morphology.disk(15)
print(np.min(roi), np.max(roi))
roi_thresh = np.copy(roi)
roi_thresh = libmag.normalize(roi_thresh, -1.0, 1.0)
print(roi_thresh)
print(np.min(roi_thresh), np.max(roi_thresh))
for i in range(roi.shape[0]):
roi_thresh[i] = filters.rank.otsu(roi_thresh[i], selem)
thresholded = roi > roi_thresh
elif thresh_type == "random_walker":
thresholded = segmenter.segment_rw(roi, size)
# dilation/erosion, adjusted based on overall intensity
thresh_mean = np.mean(thresholded)
print("thresh_mean: {}".format(thresh_mean))
selem_dil = None
selem_eros = None
if thresh_mean > 0.45:
thresholded = morphology.erosion(thresholded, morphology.cube(1))
selem_dil = morphology.ball(1)
selem_eros = morphology.octahedron(1)
elif thresh_mean > 0.35:
thresholded = morphology.erosion(thresholded, morphology.cube(2))
selem_dil = morphology.ball(2)
selem_eros = morphology.octahedron(1)
elif thresh_mean > 0.3:
selem_dil = morphology.ball(1)
selem_eros = morphology.cube(5)
elif thresh_mean > 0.1:
selem_dil = morphology.ball(1)
selem_eros = morphology.cube(4)
elif thresh_mean > 0.05:
selem_dil = morphology.octahedron(2)
selem_eros = morphology.octahedron(2)
else:
selem_dil = morphology.octahedron(1)
selem_eros = morphology.octahedron(2)
if selem_dil is not None:
thresholded = morphology.dilation(thresholded, selem_dil)
if selem_eros is not None:
thresholded = morphology.erosion(thresholded, selem_eros)
return thresholded
def plot_3d_surface(roi, scene_mlab, channel, segment=False, flipz=False):
"""Plots areas with greater intensity as 3D surfaces.
Args:
roi (:obj:`np.ndarray`): Region of interest either as a 3D (z, y, x) or
4D (z, y, x, channel) ndarray.
scene_mlab (:mod:``mayavi.mlab``): Mayavi mlab module. Any
current image will be cleared first.
channel (int): Channel to select, which can be None to indicate all
channels.
segment (bool): True to denoise and segment ``roi`` before displaying,
which may remove artifacts that might otherwise lead to
spurious surfaces. Defaults to False.
flipz: True to invert ``roi`` along z-axis to match handedness
of Matplotlib with z progressing upward; defaults to False.
"""
# Plot in Mayavi
#mlab.figure()
print("viewing 3D surface")
pipeline = scene_mlab.pipeline
scene_mlab.clf()
settings = config.roi_profile
if flipz:
# invert along z-axis to match handedness of Matplotlib with z up
roi = roi[::-1]
# saturate to remove noise and normalize values
roi = saturate_roi(roi, channel=channel)
# turn off segmentation if ROI too big (arbitrarily set here as
# > 10 million pixels) to avoid performance hit and since likely showing
# large region of downsampled image anyway, where don't need hi res
num_pixels = np.prod(roi.shape)
to_segment = num_pixels < 10000000
time_start = time()
multichannel, channels = setup_channels(roi, channel, 3)
for chl in channels:
roi_show = roi[..., chl] if multichannel else roi
# clip to minimize sub-nuclear variation
roi_show = np.clip(roi_show, 0.2, 0.8)
if segment:
# denoising makes for much cleaner images but also seems to allow
# structures to blend together. TODO: consider segmented individual
# structures and rendering as separate surfaces to avoid blending
roi_show = restoration.denoise_tv_chambolle(roi_show, weight=0.1)
# build surface from segmented ROI
if to_segment:
vmin, vmax = np.percentile(roi_show, (40, 70))
walker = segmenter.segment_rw(roi_show,
chl,
vmin=vmin,
vmax=vmax)
roi_show *= np.subtract(walker[0], 1)
else:
print("deferring segmentation as {} px is above threshold".
format(num_pixels))
# ROI is in (z, y, x) order, so need to transpose or swap x,z axes
roi_show = np.transpose(roi_show)
surface = pipeline.scalar_field(roi_show)
# Contour -> Surface pipeline
# create the surface
surface = pipeline.contour(surface)
# remove many more extraneous points
surface = pipeline.user_defined(surface, filter="SmoothPolyDataFilter")
surface.filter.number_of_iterations = 400
surface.filter.relaxation_factor = 0.015
# distinguishing pos vs neg curvatures?
surface = pipeline.user_defined(surface, filter="Curvatures")
surface = scene_mlab.pipeline.surface(surface)
module_manager = surface.module_manager
module_manager.scalar_lut_manager.data_range = np.array([-2, 0])
module_manager.scalar_lut_manager.lut_mode = "gray"
'''
# Surface pipleline with contours enabled (similar to above?)
surface = pipeline.contour_surface(
surface, color=(0.7, 1, 0.7), line_width=6.0)
surface.actor.property.representation = 'wireframe'
#surface.actor.property.line_width = 6.0
surface.actor.mapper.scalar_visibility = False
'''
'''
# IsoSurface pipeline
# uses unique IsoSurface module but appears to have
# similar output to contour_surface
surface = pipeline.iso_surface(surface)
# limit contours for simpler surfaces including smaller file sizes;
# TODO: consider making settable as arg or through profile
surface.contour.number_of_contours = 1
try:
# increase min to further reduce complexity
surface.contour.minimum_contour = 0.5
surface.contour.maximum_contour = 0.8
except Exception as e:
print(e)
print("ignoring min/max contour for now")
'''
_resize_glyphs_isotropic(settings, surface)
print("time to render 3D surface: {}".format(time() - time_start))