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!important;box-shadow:none !important;text-shadow:none !important}a[href]:after{content:" (" attr(href) ")";font-size:90%}a[href][title]:after{content:none}abbr[title]:after{content:" (" attr(title) ")"}.ir a:after,a[href^="javascript:"]:after,a[href^="#"]:after{content:""}pre,blockquote{border:1px solid #999;page-break-inside:avoid}thead{display:table-header-group}tr,img{page-break-inside:avoid}img{max-width:100% !important}@page{margin:0.5cm}p,h2,h3{orphans:3;widows:3}h1,h2,h3,h4,h5,h6{page-break-after:avoid}}</style> +<script defer src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/10.1.1/highlight.min.js" integrity="sha256-Uv3H6lx7dJmRfRvH8TH6kJD1TSK1aFcwgx+mdg3epi8=" crossorigin></script> +<script>window.addEventListener('DOMContentLoaded', () => hljs.initHighlighting())</script> +</head> +<body> +<main> +<article id="content"> +<header> +<h1 class="title">Module <code>pymskt.mesh.createMesh</code></h1> +</header> +<section id="section-intro"> +<details class="source"> +<summary> +<span>Expand source code</span> +</summary> +<pre><code class="python">import os +import vtk +import SimpleITK as sitk + +import pymskt.image as msktimage +import pymskt.mesh.meshTransform as meshTransform +from pymskt.utils import safely_delete_tmp_file + +def discrete_marching_cubes(vtk_image_reader, + n_labels=1, + start_label=1, + end_label=1, + compute_normals_on=True, + return_polydata=True + ): + """ + Compute dmc on segmentation image. + Creates a surface mesh (polydata) that closely covers binary (discrete) segmentations. + + Parameters + ---------- + vtk_image_reader : vtk.Filter + VTK Filter pipeline to apply discrete marching cubes to. + n_labels : int, optional + Number of labes to create mesh for, by default 1 + start_label : int, optional + Starting index of labels to mesh, by default 1 + end_label : int, optional + Ending index of labels to mesh, by default 1 + compute_normals_on : bool, optional + Calculate normals to surface, by default True + return_polydata : bool, optional + Whether to return a vtk.polydata or not (`vtk.Filter` pipeline instead), by default True + + Returns + ------- + vtk.Filter Pipeline + Returns a pipeline which more functions can be chained too - this improves performance. + + OR + + vtk.Polydata + Returns a polydata (surface mesh). + + """ + + dmc = vtk.vtkDiscreteMarchingCubes() + dmc.SetInputConnection(vtk_image_reader.GetOutputPort()) + if compute_normals_on is True: + dmc.ComputeNormalsOn() + dmc.GenerateValues(n_labels, start_label, end_label) + dmc.Update() + + if return_polydata is True: + return dmc.GetOutput() + elif return_polydata is False: + return dmc + + +def continuous_marching_cubes(vtk_image_reader, + threshold=0.5, + compute_normals_on=True, + compute_gradients_on=True, + return_polydata=True): + """ + - Compute a continuous marching cubes on a segmentation mask. + - Enables defining the surface based on a contour set to a floating point cutoff. + + + Parameters + ---------- + vtk_image_reader : vtk.Filter + This is the output of a `vtk.Filter` from a previous step. E.g., output of pymskt.image.read_nrrd(). + + threshold : float, optional + Floating point value to create surface mesh, by default 0.5 + compute_normals_on : bool, optional + Whether or not to compute surface normals for mesh, by default True + compute_gradients_on : bool, optional + Whether or not to compute gradients over mesh surface, by default True + return_polydata : bool, optional + Whether to return a vtk.polydata or not (VTK filter pipeline instead e.g., `mc`), by default True + + Returns + ------- + vtk.Filter Pipeline + Returns a pipeline which more functions can be chained too - this improves performance. + + OR + + vtk.Polydata + Returns a polydata (surface mesh). + """ + mc = vtk.vtkMarchingContourFilter() + mc.SetInputConnection(vtk_image_reader.GetOutputPort()) + if compute_normals_on is True: + mc.ComputeNormalsOn() + elif compute_normals_on is False: + mc.ComputeNormalsOff() + + if compute_gradients_on is True: + mc.ComputeGradientsOn() + elif compute_gradients_on is False: + mc.ComputeGradientsOff() + mc.SetValue(0, threshold) + mc.Update() + + if return_polydata is True: + mesh = mc.GetOutput() + return mesh + elif return_polydata is False: + return mc + +def create_surface_mesh(seg_image, + label_idx, + image_smooth_var, + loc_tmp_save='/tmp', + tmp_filename='temp_smoothed_bone.nrrd', + copy_image_transform=True, + mc_threshold=0.5, + filter_binary_image=True): + """ + Create surface mesh. + Option to filter binary image to get smoother surface representation. + + Parameters + ---------- + seg_image : SimpleITK.Image + Segmentation image to be filtered and meshed with marching cubes. + label_idx : int + What anatomical label to be meshed. + image_smooth_var : float + Variance to apply a gaussian smoothing function to. + loc_tmp_save : str, optional + Location to save temporary files for passing SimpleITK.Image to vtk functions, by default '/tmp' + tmp_filename : str, optional + Filename of saved temporary file, by default 'temp_smoothed_bone.nrrd' + copy_image_transform : bool, optional + Whether or not to apply image transform to final mesh or to leave it at origin, by default True + mc_threshold : float, optional + What floating point value to create surface mesh at, by default 0.5 + filter_binary_image : bool, optional + Should the binary image be filtered (smoothed) or not. + + Returns + ------- + vtk.Polydata + Surface mesh created using a continuous cutoff `mc_threshold` after applying + gaussian smoothing with variance = `image_smooth_var`. + """ + + # Set border of segmentation to 0 so that segs are all closed. + seg_image = msktimage.set_seg_border_to_zeros(seg_image, border_size=1) + + if filter_binary_image is True: + # smooth/filter the image to get a better surface. + seg_image = msktimage.smooth_image(seg_image, label_idx, image_smooth_var) + else: + seg_image = msktimage.binarize_segmentation_image(seg_image, label_idx) + # save filtered image to disk so can read it in using vtk nrrd reader + sitk.WriteImage(seg_image, os.path.join(loc_tmp_save, tmp_filename)) + smoothed_nrrd_reader = msktimage.read_nrrd(os.path.join(loc_tmp_save, tmp_filename), + set_origin_zero=True) + # create the mesh using continuous marching cubes applied to the smoothed binary image. + smooth_mesh = continuous_marching_cubes(smoothed_nrrd_reader, threshold=mc_threshold) + + if copy_image_transform is True: + # copy image transofrm to the image to the mesh so that when viewed (e.g. in 3D Slicer) it is aligned with image + smooth_mesh = meshTransform.copy_image_transform_to_mesh(smooth_mesh, seg_image) + + # Delete tmp files + safely_delete_tmp_file(loc_tmp_save, + tmp_filename) + return smooth_mesh</code></pre> +</details> +</section> +<section> +</section> +<section> +</section> +<section> +<h2 class="section-title" id="header-functions">Functions</h2> +<dl> +<dt id="pymskt.mesh.createMesh.continuous_marching_cubes"><code class="name flex"> +<span>def <span class="ident">continuous_marching_cubes</span></span>(<span>vtk_image_reader, threshold=0.5, compute_normals_on=True, compute_gradients_on=True, return_polydata=True)</span> +</code></dt> +<dd> +<div class="desc"><ul> +<li>Compute a continuous marching cubes on a segmentation mask. </li> +<li>Enables defining the surface based on a contour set to a floating point cutoff. </li> +</ul> +<h2 id="parameters">Parameters</h2> +<dl> +<dt><strong><code>vtk_image_reader</code></strong> : <code>vtk.Filter</code></dt> +<dd>This is the output of a <code>vtk.Filter</code> from a previous step. E.g., output of pymskt.image.read_nrrd().</dd> +<dt><strong><code>threshold</code></strong> : <code>float</code>, optional</dt> +<dd>Floating point value to create surface mesh, by default 0.5</dd> +<dt><strong><code>compute_normals_on</code></strong> : <code>bool</code>, optional</dt> +<dd>Whether or not to compute surface normals for mesh, by default True</dd> +<dt><strong><code>compute_gradients_on</code></strong> : <code>bool</code>, optional</dt> +<dd>Whether or not to compute gradients over mesh surface, by default True</dd> +<dt><strong><code>return_polydata</code></strong> : <code>bool</code>, optional</dt> +<dd>Whether to return a vtk.polydata or not (VTK filter pipeline instead e.g., <code>mc</code>), by default True</dd> +</dl> +<h2 id="returns">Returns</h2> +<dl> +<dt><code>vtk.Filter Pipeline</code></dt> +<dd>Returns a pipeline which more functions can be chained too - this improves performance.</dd> +<dt><code>OR</code></dt> +<dd> </dd> +<dt><code>vtk.Polydata</code></dt> +<dd>Returns a polydata (surface mesh).</dd> +</dl></div> +<details class="source"> +<summary> +<span>Expand source code</span> +</summary> +<pre><code class="python">def continuous_marching_cubes(vtk_image_reader, + threshold=0.5, + compute_normals_on=True, + compute_gradients_on=True, + return_polydata=True): + """ + - Compute a continuous marching cubes on a segmentation mask. + - Enables defining the surface based on a contour set to a floating point cutoff. + + + Parameters + ---------- + vtk_image_reader : vtk.Filter + This is the output of a `vtk.Filter` from a previous step. E.g., output of pymskt.image.read_nrrd(). + + threshold : float, optional + Floating point value to create surface mesh, by default 0.5 + compute_normals_on : bool, optional + Whether or not to compute surface normals for mesh, by default True + compute_gradients_on : bool, optional + Whether or not to compute gradients over mesh surface, by default True + return_polydata : bool, optional + Whether to return a vtk.polydata or not (VTK filter pipeline instead e.g., `mc`), by default True + + Returns + ------- + vtk.Filter Pipeline + Returns a pipeline which more functions can be chained too - this improves performance. + + OR + + vtk.Polydata + Returns a polydata (surface mesh). + """ + mc = vtk.vtkMarchingContourFilter() + mc.SetInputConnection(vtk_image_reader.GetOutputPort()) + if compute_normals_on is True: + mc.ComputeNormalsOn() + elif compute_normals_on is False: + mc.ComputeNormalsOff() + + if compute_gradients_on is True: + mc.ComputeGradientsOn() + elif compute_gradients_on is False: + mc.ComputeGradientsOff() + mc.SetValue(0, threshold) + mc.Update() + + if return_polydata is True: + mesh = mc.GetOutput() + return mesh + elif return_polydata is False: + return mc</code></pre> +</details> +</dd> +<dt id="pymskt.mesh.createMesh.create_surface_mesh"><code class="name flex"> +<span>def <span class="ident">create_surface_mesh</span></span>(<span>seg_image, label_idx, image_smooth_var, loc_tmp_save='/tmp', tmp_filename='temp_smoothed_bone.nrrd', copy_image_transform=True, mc_threshold=0.5, filter_binary_image=True)</span> +</code></dt> +<dd> +<div class="desc"><p>Create surface mesh. +Option to filter binary image to get smoother surface representation.</p> +<h2 id="parameters">Parameters</h2> +<dl> +<dt><strong><code>seg_image</code></strong> : <code>SimpleITK.Image</code></dt> +<dd>Segmentation image to be filtered and meshed with marching cubes.</dd> +<dt><strong><code>label_idx</code></strong> : <code>int</code></dt> +<dd>What anatomical label to be meshed.</dd> +<dt><strong><code>image_smooth_var</code></strong> : <code>float</code></dt> +<dd>Variance to apply a gaussian smoothing function to.</dd> +<dt><strong><code>loc_tmp_save</code></strong> : <code>str</code>, optional</dt> +<dd>Location to save temporary files for passing SimpleITK.Image to vtk functions, by default '/tmp'</dd> +<dt><strong><code>tmp_filename</code></strong> : <code>str</code>, optional</dt> +<dd>Filename of saved temporary file, by default 'temp_smoothed_bone.nrrd'</dd> +<dt><strong><code>copy_image_transform</code></strong> : <code>bool</code>, optional</dt> +<dd>Whether or not to apply image transform to final mesh or to leave it at origin, by default True</dd> +<dt><strong><code>mc_threshold</code></strong> : <code>float</code>, optional</dt> +<dd>What floating point value to create surface mesh at, by default 0.5</dd> +<dt><strong><code>filter_binary_image</code></strong> : <code>bool</code>, optional</dt> +<dd>Should the binary image be filtered (smoothed) or not.</dd> +</dl> +<h2 id="returns">Returns</h2> +<dl> +<dt><code>vtk.Polydata</code></dt> +<dd>Surface mesh created using a continuous cutoff <code>mc_threshold</code> after applying +gaussian smoothing with variance = <code>image_smooth_var</code>.</dd> +</dl></div> +<details class="source"> +<summary> +<span>Expand source code</span> +</summary> +<pre><code class="python">def create_surface_mesh(seg_image, + label_idx, + image_smooth_var, + loc_tmp_save='/tmp', + tmp_filename='temp_smoothed_bone.nrrd', + copy_image_transform=True, + mc_threshold=0.5, + filter_binary_image=True): + """ + Create surface mesh. + Option to filter binary image to get smoother surface representation. + + Parameters + ---------- + seg_image : SimpleITK.Image + Segmentation image to be filtered and meshed with marching cubes. + label_idx : int + What anatomical label to be meshed. + image_smooth_var : float + Variance to apply a gaussian smoothing function to. + loc_tmp_save : str, optional + Location to save temporary files for passing SimpleITK.Image to vtk functions, by default '/tmp' + tmp_filename : str, optional + Filename of saved temporary file, by default 'temp_smoothed_bone.nrrd' + copy_image_transform : bool, optional + Whether or not to apply image transform to final mesh or to leave it at origin, by default True + mc_threshold : float, optional + What floating point value to create surface mesh at, by default 0.5 + filter_binary_image : bool, optional + Should the binary image be filtered (smoothed) or not. + + Returns + ------- + vtk.Polydata + Surface mesh created using a continuous cutoff `mc_threshold` after applying + gaussian smoothing with variance = `image_smooth_var`. + """ + + # Set border of segmentation to 0 so that segs are all closed. + seg_image = msktimage.set_seg_border_to_zeros(seg_image, border_size=1) + + if filter_binary_image is True: + # smooth/filter the image to get a better surface. + seg_image = msktimage.smooth_image(seg_image, label_idx, image_smooth_var) + else: + seg_image = msktimage.binarize_segmentation_image(seg_image, label_idx) + # save filtered image to disk so can read it in using vtk nrrd reader + sitk.WriteImage(seg_image, os.path.join(loc_tmp_save, tmp_filename)) + smoothed_nrrd_reader = msktimage.read_nrrd(os.path.join(loc_tmp_save, tmp_filename), + set_origin_zero=True) + # create the mesh using continuous marching cubes applied to the smoothed binary image. + smooth_mesh = continuous_marching_cubes(smoothed_nrrd_reader, threshold=mc_threshold) + + if copy_image_transform is True: + # copy image transofrm to the image to the mesh so that when viewed (e.g. in 3D Slicer) it is aligned with image + smooth_mesh = meshTransform.copy_image_transform_to_mesh(smooth_mesh, seg_image) + + # Delete tmp files + safely_delete_tmp_file(loc_tmp_save, + tmp_filename) + return smooth_mesh</code></pre> +</details> +</dd> +<dt id="pymskt.mesh.createMesh.discrete_marching_cubes"><code class="name flex"> +<span>def <span class="ident">discrete_marching_cubes</span></span>(<span>vtk_image_reader, n_labels=1, start_label=1, end_label=1, compute_normals_on=True, return_polydata=True)</span> +</code></dt> +<dd> +<div class="desc"><p>Compute dmc on segmentation image. +Creates a surface mesh (polydata) that closely covers binary (discrete) segmentations.</p> +<h2 id="parameters">Parameters</h2> +<dl> +<dt><strong><code>vtk_image_reader</code></strong> : <code>vtk.Filter</code></dt> +<dd>VTK Filter pipeline to apply discrete marching cubes to.</dd> +<dt><strong><code>n_labels</code></strong> : <code>int</code>, optional</dt> +<dd>Number of labes to create mesh for, by default 1</dd> +<dt><strong><code>start_label</code></strong> : <code>int</code>, optional</dt> +<dd>Starting index of labels to mesh, by default 1</dd> +<dt><strong><code>end_label</code></strong> : <code>int</code>, optional</dt> +<dd>Ending index of labels to mesh, by default 1</dd> +<dt><strong><code>compute_normals_on</code></strong> : <code>bool</code>, optional</dt> +<dd>Calculate normals to surface, by default True</dd> +<dt><strong><code>return_polydata</code></strong> : <code>bool</code>, optional</dt> +<dd>Whether to return a vtk.polydata or not (<code>vtk.Filter</code> pipeline instead), by default True</dd> +</dl> +<h2 id="returns">Returns</h2> +<dl> +<dt><code>vtk.Filter Pipeline</code></dt> +<dd>Returns a pipeline which more functions can be chained too - this improves performance.</dd> +<dt><code>OR</code></dt> +<dd> </dd> +<dt><code>vtk.Polydata</code></dt> +<dd>Returns a polydata (surface mesh).</dd> +</dl></div> +<details class="source"> +<summary> +<span>Expand source code</span> +</summary> +<pre><code class="python">def discrete_marching_cubes(vtk_image_reader, + n_labels=1, + start_label=1, + end_label=1, + compute_normals_on=True, + return_polydata=True + ): + """ + Compute dmc on segmentation image. + Creates a surface mesh (polydata) that closely covers binary (discrete) segmentations. + + Parameters + ---------- + vtk_image_reader : vtk.Filter + VTK Filter pipeline to apply discrete marching cubes to. + n_labels : int, optional + Number of labes to create mesh for, by default 1 + start_label : int, optional + Starting index of labels to mesh, by default 1 + end_label : int, optional + Ending index of labels to mesh, by default 1 + compute_normals_on : bool, optional + Calculate normals to surface, by default True + return_polydata : bool, optional + Whether to return a vtk.polydata or not (`vtk.Filter` pipeline instead), by default True + + Returns + ------- + vtk.Filter Pipeline + Returns a pipeline which more functions can be chained too - this improves performance. + + OR + + vtk.Polydata + Returns a polydata (surface mesh). + + """ + + dmc = vtk.vtkDiscreteMarchingCubes() + dmc.SetInputConnection(vtk_image_reader.GetOutputPort()) + if compute_normals_on is True: + dmc.ComputeNormalsOn() + dmc.GenerateValues(n_labels, start_label, end_label) + dmc.Update() + + if return_polydata is True: + return dmc.GetOutput() + elif return_polydata is False: + return dmc</code></pre> +</details> +</dd> +</dl> +</section> +<section> +</section> +</article> +<nav id="sidebar"> +<h1>Index</h1> +<div class="toc"> +<ul></ul> +</div> +<ul id="index"> +<li><h3>Super-module</h3> +<ul> +<li><code><a title="pymskt.mesh" href="index.html">pymskt.mesh</a></code></li> +</ul> +</li> +<li><h3><a href="#header-functions">Functions</a></h3> +<ul class=""> +<li><code><a title="pymskt.mesh.createMesh.continuous_marching_cubes" href="#pymskt.mesh.createMesh.continuous_marching_cubes">continuous_marching_cubes</a></code></li> +<li><code><a title="pymskt.mesh.createMesh.create_surface_mesh" href="#pymskt.mesh.createMesh.create_surface_mesh">create_surface_mesh</a></code></li> +<li><code><a title="pymskt.mesh.createMesh.discrete_marching_cubes" href="#pymskt.mesh.createMesh.discrete_marching_cubes">discrete_marching_cubes</a></code></li> +</ul> +</li> +</ul> +</nav> +</main> +<footer id="footer"> +<p>Generated by <a href="https://pdoc3.github.io/pdoc" title="pdoc: Python API documentation generator"><cite>pdoc</cite> 0.10.0</a>.</p> +</footer> +</body> +</html> \ No newline at end of file