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diff --git a/EMBRYOS.md b/EMBRYOS.md
@@ -3,5 +3,6 @@
 ## Ascadian Embryo
 In this example we consider a dataset imaged using Light sheet fused from four angles to create a single channel 3D image of Phallusia Mammillata Embryo created using live SPIM imaging. The training data can be found [here](https://figshare.com/articles/dataset/Astec-half-Pm1_Cut_at_2-cell_stage_half_Phallusia_mammillata_embryo_live_SPIM_imaging_stages_6-16_/11309570?backTo=/s/765d4361d1b073beedd5). For this imaging modality we trained only a [UNet model](https://zenodo.org/record/6337699) to segment the interior region of the cells and by using ```slice_merge=True``` and 
 ```expand_labels=True``` in the VollSeg parameter setting we obtained the following segmentation result along with the metrics compared to the ground truth.
-<img src="https://github.com/kapoorlab/vollseg-napari/blob/main/vollseg_napari/images/Ascadian_raw.png"  title="Raw Ascadian Embryo" width="200">
-<img src="https://github.com/kapoorlab/vollseg-napari/blob/main/vollseg_napari/images/Ascadian_pred.png" title="Prediction Ascadian Embryo" width="200" > | <img src="https://github.com/kapoorlab/vollseg-napari/blob/main/vollseg_napari/images/Metrics_Ascadian.png" title="Metrics Ascadian Embryo" width="200" > 
+| Raw Ascadian Embryo | Prediction Ascadian Embryo | Metrics Ascadian Embryo |
+|:-------------------:|:--------------------------:|:-----------------------:|
+| ![Raw Ascadian Embryo](images/Ascadian_raw.png) | ![Prediction Ascadian Embryo](images/Ascadian_pred.png) | ![Metrics Ascadian Embryo](images/Metrics_Ascadian.png) |
diff --git a/MAMMARYGLAND.md b/MAMMARYGLAND.md
@@ -1,3 +1,3 @@
 # Segmentation of mammary gland cells
 
-VollSeg specializes with its seed pooling approach to segment irregular shapes of [mammary gland cells](https://github.com/kapoorlab/VollSeg/blob/main/images/Seg_pipe-git.png) from human or mouse samples. In the orignal algorithm we use a CARE trained denoising model and eaither use the U-Net model for semantic segmentation or use the denoising model for the semantic segmentation depending on which model has a better prediction. For using combination of (U-Net, CARE and StarDist) model with U-Net as the model for semantic segmentation use this [script](scripts/mammary_gland_us.py) if you want to use the denoised image as the base image for creating the semantic segmentation map using Otsu threshold set the parameter ```dounet=False``` in that same script.
+VollSeg specializes with its seed pooling approach to segment irregular shapes of [mammary gland cells](images/Seg_pipe-git.png) from human or mouse samples. In the orignal algorithm we use a CARE trained denoising model and eaither use the U-Net model for semantic segmentation or use the denoising model for the semantic segmentation depending on which model has a better prediction. For using combination of (U-Net, CARE and StarDist) model with U-Net as the model for semantic segmentation use this [script](scripts/mammary_gland_us.py) if you want to use the denoised image as the base image for creating the semantic segmentation map using Otsu threshold set the parameter ```dounet=False``` in that same script.
diff --git a/_build/.doctrees/EMBRYOS.doctree b/_build/.doctrees/EMBRYOS.doctree
diff --git a/_build/.doctrees/MAMMARYGLAND.doctree b/_build/.doctrees/MAMMARYGLAND.doctree
diff --git a/_build/.doctrees/MICROTUBULES.doctree b/_build/.doctrees/MICROTUBULES.doctree
diff --git a/_build/.doctrees/README.doctree b/_build/.doctrees/README.doctree
diff --git a/_build/.doctrees/SPHEROIDS.doctree b/_build/.doctrees/SPHEROIDS.doctree
diff --git a/_build/.doctrees/XENOPUS.doctree b/_build/.doctrees/XENOPUS.doctree
diff --git a/_build/.doctrees/environment.pickle b/_build/.doctrees/environment.pickle
diff --git a/_build/html/.buildinfo b/_build/html/.buildinfo
@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 60ced9f3b72bc1b8f68bf692be8c3eec
+config: 29c0c89e03c24784a4e7094abc75d95c
 tags: 645f666f9bcd5a90fca523b33c5a78b7
diff --git a/_build/html/EMBRYOS.html b/_build/html/EMBRYOS.html
@@ -63,7 +63,7 @@
     <script>DOCUMENTATION_OPTIONS.pagename = 'EMBRYOS';</script>
     <link rel="index" title="Index" href="genindex.html" />
     <link rel="search" title="Search" href="search.html" />
-    <link rel="next" title="Xenopus joint Nuclei and Membrane Segmentation" href="XENOPUS.html" />
+    <link rel="next" title="Segmentation of mammary gland cells" href="MAMMARYGLAND.html" />
     <link rel="prev" title="VollSeg Napari Plugin" href="README.html" />
   <meta name="viewport" content="width=device-width, initial-scale=1"/>
   <meta name="docsearch:language" content="None"/>
@@ -135,8 +135,14 @@
 
 
 
+
+
+
+
+
+    <img src="_static/kapoorlogo.png" class="logo__image only-light" alt="Logo image"/>
+    <script>document.write(`<img src="_static/kapoorlogo.png" class="logo__image only-dark" alt="Logo image"/>`);</script>
 
-    <p class="title logo__title">Segmentation using VollSeg</p>
 
 </a></div>
         <div class="sidebar-primary-item"><nav class="bd-links" id="bd-docs-nav" aria-label="Main">
@@ -151,8 +157,10 @@
         </ul>
         <ul class="current nav bd-sidenav">
 <li class="toctree-l1 current active"><a class="current reference internal" href="#">Confocal and Light Sheet imaged Embryonic cells</a></li>
+<li class="toctree-l1"><a class="reference internal" href="MAMMARYGLAND.html">Segmentation of mammary gland cells</a></li>
 <li class="toctree-l1"><a class="reference internal" href="XENOPUS.html">Xenopus joint Nuclei and Membrane Segmentation</a></li>
 <li class="toctree-l1"><a class="reference internal" href="SPHEROIDS.html">Spheroids joint Nuclei and Membrane Segmentation</a></li>
+<li class="toctree-l1"><a class="reference internal" href="MICROTUBULES.html">Segmentation of Microtubule and Actin Kymographs</a></li>
 </ul>
 
     </div>
@@ -363,9 +371,21 @@ <h1>Confocal and Light Sheet imaged Embryonic cells<a class="headerlink" href="#
 <section id="ascadian-embryo">
 <h2>Ascadian Embryo<a class="headerlink" href="#ascadian-embryo" title="Permalink to this headline">#</a></h2>
 <p>In this example we consider a dataset imaged using Light sheet fused from four angles to create a single channel 3D image of Phallusia Mammillata Embryo created using live SPIM imaging. The training data can be found <a class="reference external" href="https://figshare.com/articles/dataset/Astec-half-Pm1_Cut_at_2-cell_stage_half_Phallusia_mammillata_embryo_live_SPIM_imaging_stages_6-16_/11309570?backTo=/s/765d4361d1b073beedd5">here</a>. For this imaging modality we trained only a <a class="reference external" href="https://zenodo.org/record/6337699">UNet model</a> to segment the interior region of the cells and by using <code class="docutils literal notranslate"><span class="pre">slice_merge=True</span></code> and
-<code class="docutils literal notranslate"><span class="pre">expand_labels=True</span></code> in the VollSeg parameter setting we obtained the following segmentation result along with the metrics compared to the ground truth.
-<img src="https://github.com/kapoorlab/vollseg-napari/blob/main/vollseg_napari/images/Ascadian_raw.png"  title="Raw Ascadian Embryo" width="200">
-<img src="https://github.com/kapoorlab/vollseg-napari/blob/main/vollseg_napari/images/Ascadian_pred.png" title="Prediction Ascadian Embryo" width="200" > | <img src="https://github.com/kapoorlab/vollseg-napari/blob/main/vollseg_napari/images/Metrics_Ascadian.png" title="Metrics Ascadian Embryo" width="200" ></p>
+<code class="docutils literal notranslate"><span class="pre">expand_labels=True</span></code> in the VollSeg parameter setting we obtained the following segmentation result along with the metrics compared to the ground truth.</p>
+<table class="colwidths-auto table">
+<thead>
+<tr class="row-odd"><th class="text-center head"><p>Raw Ascadian Embryo</p></th>
+<th class="text-center head"><p>Prediction Ascadian Embryo</p></th>
+<th class="text-center head"><p>Metrics Ascadian Embryo</p></th>
+</tr>
+</thead>
+<tbody>
+<tr class="row-even"><td class="text-center"><p><img alt="Raw Ascadian Embryo" src="_images/Ascadian_raw.png" /></p></td>
+<td class="text-center"><p><img alt="Prediction Ascadian Embryo" src="_images/Ascadian_pred.png" /></p></td>
+<td class="text-center"><p><img alt="Metrics Ascadian Embryo" src="_images/Metrics_Ascadian.png" /></p></td>
+</tr>
+</tbody>
+</table>
 </section>
 </section>
 
@@ -410,11 +430,11 @@ <h2>Ascadian Embryo<a class="headerlink" href="#ascadian-embryo" title="Permalin
       </div>
     </a>
     <a class="right-next"
-       href="XENOPUS.html"
+       href="MAMMARYGLAND.html"
        title="next page">
       <div class="prev-next-info">
         <p class="prev-next-subtitle">next</p>
-        <p class="prev-next-title">Xenopus joint Nuclei and Membrane Segmentation</p>
+        <p class="prev-next-title">Segmentation of mammary gland cells</p>
       </div>
       <i class="fa-solid fa-angle-right"></i>
     </a>

diff --git a/_build/html/MAMMARYGLAND.html b/_build/html/MAMMARYGLAND.html
@@ -9,7 +9,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
 
-    <title>&lt;no title&gt; &#8212; Segmentation using VollSeg</title>
+    <title>Segmentation of mammary gland cells &#8212; Segmentation using VollSeg</title>
 
 
 
@@ -135,8 +135,14 @@
 
 
 
+
+
+
+
+
+    <img src="_static/kapoorlogo.png" class="logo__image only-light" alt="Logo image"/>
+    <script>document.write(`<img src="_static/kapoorlogo.png" class="logo__image only-dark" alt="Logo image"/>`);</script>
 
-    <p class="title logo__title">Segmentation using VollSeg</p>
 
 </a></div>
         <div class="sidebar-primary-item"><nav class="bd-links" id="bd-docs-nav" aria-label="Main">
@@ -149,10 +155,12 @@
                 </a>
             </li>
         </ul>
-        <ul class="nav bd-sidenav">
+        <ul class="current nav bd-sidenav">
 <li class="toctree-l1"><a class="reference internal" href="EMBRYOS.html">Confocal and Light Sheet imaged Embryonic cells</a></li>
+<li class="toctree-l1 current active"><a class="current reference internal" href="#">Segmentation of mammary gland cells</a></li>
 <li class="toctree-l1"><a class="reference internal" href="XENOPUS.html">Xenopus joint Nuclei and Membrane Segmentation</a></li>
 <li class="toctree-l1"><a class="reference internal" href="SPHEROIDS.html">Spheroids joint Nuclei and Membrane Segmentation</a></li>
+<li class="toctree-l1"><a class="reference internal" href="MICROTUBULES.html">Segmentation of Microtubule and Actin Kymographs</a></li>
 </ul>
 
     </div>
@@ -323,9 +331,7 @@
   </button>
 `);
 </script>
-<label class="sidebar-toggle secondary-toggle btn btn-sm" for="__secondary"title="Toggle secondary sidebar" data-bs-placement="bottom" data-bs-toggle="tooltip">
-    <span class="fa-solid fa-list"></span>
-</label>
+
 </div></div>
 
     </div>
@@ -336,19 +342,11 @@
 
 
 <div id="jb-print-docs-body" class="onlyprint">
-    <h1><no title></h1>
+    <h1>Segmentation of mammary gland cells</h1>
     <!-- Table of contents -->
     <div id="print-main-content">
         <div id="jb-print-toc">
 
-            <div>
-                <h2> Contents </h2>
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@@ -358,7 +356,11 @@ <h2> Contents </h2>
 <div id="searchbox"></div>
                 <article class="bd-article" role="main">
 
-
+  <section class="tex2jax_ignore mathjax_ignore" id="segmentation-of-mammary-gland-cells">
+<h1>Segmentation of mammary gland cells<a class="headerlink" href="#segmentation-of-mammary-gland-cells" title="Permalink to this headline">#</a></h1>
+<p>VollSeg specializes with its seed pooling approach to segment irregular shapes of <a class="reference download internal" download="" href="_downloads/56c50bc2bcbe8d6df651b825711326dd/Seg_pipe-git.png"><span class="xref download myst">mammary gland cells</span></a> from human or mouse samples. In the orignal algorithm we use a CARE trained denoising model and eaither use the U-Net model for semantic segmentation or use the denoising model for the semantic segmentation depending on which model has a better prediction. For using combination of (U-Net, CARE and StarDist) model with U-Net as the model for semantic segmentation use this <a class="reference download internal" download="" href="_downloads/55ced61326261fee22b55dba8817fd8e/mammary_gland_us.py"><span class="xref download myst">script</span></a> if you want to use the denoised image as the base image for creating the semantic segmentation map using Otsu threshold set the parameter <code class="docutils literal notranslate"><span class="pre">dounet=False</span></code> in that same script.</p>
+</section>
+
     <script type="text/x-thebe-config">
     {
         requestKernel: true,
@@ -418,20 +420,6 @@ <h2> Contents </h2>
 
 
 
-                <div class="bd-sidebar-secondary bd-toc"><div class="sidebar-secondary-items sidebar-secondary__inner">
-
-  <div class="sidebar-secondary-item">
-  <div class="page-toc tocsection onthispage">
-    <i class="fa-solid fa-list"></i> Contents
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diff --git a/_build/html/MICROTUBULES.html b/_build/html/MICROTUBULES.html
@@ -9,7 +9,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
 
-    <title>&lt;no title&gt; &#8212; Segmentation using VollSeg</title>
+    <title>Segmentation of Microtubule and Actin Kymographs &#8212; Segmentation using VollSeg</title>
 
 
 
@@ -134,8 +134,14 @@
 
 
 
+
+
+
+
+
+    <img src="_static/kapoorlogo.png" class="logo__image only-light" alt="Logo image"/>
+    <script>document.write(`<img src="_static/kapoorlogo.png" class="logo__image only-dark" alt="Logo image"/>`);</script>
 
-    <p class="title logo__title">Segmentation using VollSeg</p>
 
 </a></div>
         <div class="sidebar-primary-item"><nav class="bd-links" id="bd-docs-nav" aria-label="Main">
@@ -148,10 +154,12 @@
                 </a>
             </li>
         </ul>
-        <ul class="nav bd-sidenav">
+        <ul class="current nav bd-sidenav">
 <li class="toctree-l1"><a class="reference internal" href="EMBRYOS.html">Confocal and Light Sheet imaged Embryonic cells</a></li>
+<li class="toctree-l1"><a class="reference internal" href="MAMMARYGLAND.html">Segmentation of mammary gland cells</a></li>
 <li class="toctree-l1"><a class="reference internal" href="XENOPUS.html">Xenopus joint Nuclei and Membrane Segmentation</a></li>
 <li class="toctree-l1"><a class="reference internal" href="SPHEROIDS.html">Spheroids joint Nuclei and Membrane Segmentation</a></li>
+<li class="toctree-l1 current active"><a class="current reference internal" href="#">Segmentation of Microtubule and Actin Kymographs</a></li>
 </ul>
 
     </div>
@@ -322,9 +330,7 @@
   </button>
 `);
 </script>
-<label class="sidebar-toggle secondary-toggle btn btn-sm" for="__secondary"title="Toggle secondary sidebar" data-bs-placement="bottom" data-bs-toggle="tooltip">
-    <span class="fa-solid fa-list"></span>
-</label>
+
 </div></div>
 
     </div>
@@ -335,19 +341,11 @@
 
 
 <div id="jb-print-docs-body" class="onlyprint">
-    <h1><no title></h1>
+    <h1>Segmentation of Microtubule and Actin Kymographs</h1>
     <!-- Table of contents -->
     <div id="print-main-content">
         <div id="jb-print-toc">
 
-            <div>
-                <h2> Contents </h2>
-            </div>
-            <nav aria-label="Page">
-                <ul class="simple visible nav section-nav flex-column">
-</ul>
-
-            </nav>
         </div>
     </div>
 </div>
@@ -357,7 +355,10 @@ <h2> Contents </h2>
 <div id="searchbox"></div>
                 <article class="bd-article" role="main">
 
-
+  <section class="tex2jax_ignore mathjax_ignore" id="segmentation-of-microtubule-and-actin-kymographs">
+<h1>Segmentation of Microtubule and Actin Kymographs<a class="headerlink" href="#segmentation-of-microtubule-and-actin-kymographs" title="Permalink to this headline">#</a></h1>
+</section>
+
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@@ -408,20 +409,6 @@ <h2> Contents </h2>
 
 
 
-                <div class="bd-sidebar-secondary bd-toc"><div class="sidebar-secondary-items sidebar-secondary__inner">
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-  <div class="page-toc tocsection onthispage">
-    <i class="fa-solid fa-list"></i> Contents
-  </div>
-  <nav class="bd-toc-nav page-toc">
-    <ul class="simple visible nav section-nav flex-column">
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