various typo fixes and edits for 38 39 41 (resolves #50)

Author: N3llz

Diff for: htdocs/BBBC038/index.html

@@ -100,7 +100,6 @@ <h3>Ground truth </h3>
         <a href="https://github.com/ibmua/data-science-bowl-2018-train-set">[Data science bowl 2018 training set improved (Github repo)]</a><br>
         <a href="https://github.com/lopuhin/kaggle-dsbowl-2018-dataset-fixes">[Kaggle Data Science Bowl 2018 dataset fixes (Github repo)]</a>
     <h3>For more information</h3>
-   <p>These images were curated from a variety of sources by the Imaging Platform at the Broad Institute for the 2018 Data Science Bowl. Please contact the <a href="mailto:[email protected]">Imaging Platform</a>.</p>
    <p>These images were curated from a variety of sources (below) by the Imaging Platform at the Broad Institute for the 2018 Data Science Bowl. Please contact the <a href="mailto:[email protected]">Imaging Platform</a> with any inquiries.</p>
    <h4>Contributors</h4>
    <ul>
@@ -122,7 +121,7 @@ <h4>Contributors</h4>
        <li>several biologists who wished to remain anonymous</li>
        <li>And of course, the Carpenter lab, Broad Institute</li>
    </ul>
-    
+
 
 
     <h3>Published results using this image set</h3>

Diff for: htdocs/BBBC039/index.html

@@ -85,6 +85,7 @@ <h3>Images</h3>
     <p>This data set has a total of 200 fields of view of nuclei captured with fluorescence microscopy using the Hoechst stain. These images are a sample of the larger BBBC022 chemical screen. The images are stored as TIFF files with 520x696 pixels at 16 bits.</p>
     <p><a href="https://github.com/carpenterlab/unet4nuclei">Github repo</a></p>
     <p><a href="images.zip"><i class="icon-download-alt"></i> images.zip (77.9 MB)</a></p>
+    <p>A small fraction of the images in this dataset overlap with the BBBC038 collection, which is the Data Science Bowl 2018 dataset. Not all images in this dataset were included in the DSB 2018 challenge to avoid a dominant number of fluorescent images for the competition. The BBBC038 collection has more variety of experimental conditions, whereas this dataset comes from a single high-throughput experiment with a large number of perturbations.</p>
 
     <h3>Ground truth </h3>
     <p>Ground truth annotations are stored as PNG files encoding masks of independent nuclei: if two nuclei touch, they are labeled with a different color. These annotations need to be decoded into labelled matrices to be used as ground truth. Example code for decoding masks can be found in this <a href="https://gist.github.com/jccaicedo/15e811722fca51e3ae90e8b43057f075">gist</a>.</p>

Diff for: htdocs/BBBC041/index.html

@@ -86,7 +86,7 @@ <h3>Ground truth </h3>
 
     <h3>For more information</h3>
     <p><p>These images were contributed by <a href="mailto:[email protected]">Jane Hung</a> of MIT and the Broad Institute in Cambridge, MA.</p>
-
+    <p>There is also a <a href="https://github.com/tobsecret/Awesome_Malaria_Parasite_Imaging_Datasets">Github reposity</a> that lists malaria parasite imaging datasets (blood smears).</p>
 
     <h3>Published results using this image set</h3>
     <p>These datasets will be evaluated in a publication to be submitted. </p>

Diff for: make.py

@@ -56,7 +56,6 @@ def icons(base):
               'BBBC037': u'Human U2OS cells - Gene overexpression profiling experiment',
               'BBBC038': u'Kaggle 2018 Data Science Bowl',
               'BBBC039': u'Nuclei of U2OS cells in a chemical screen',
-              'BBBC040': u'Human U2OS cells – Small molecule Cell Painting experiment',
               'BBBC041': u'P. vivax (malaria) infected human blood smears',
 }
 

Diff for: templates/BBBC038.html

@@ -50,7 +50,6 @@ <h3>Ground truth {{O}}</h3>
         <a href="https://github.com/ibmua/data-science-bowl-2018-train-set">[Data science bowl 2018 training set improved (Github repo)]</a><br>
         <a href="https://github.com/lopuhin/kaggle-dsbowl-2018-dataset-fixes">[Kaggle Data Science Bowl 2018 dataset fixes (Github repo)]</a>
     <h3>For more information</h3>
-   <p>These images were curated from a variety of sources by the Imaging Platform at the Broad Institute for the 2018 Data Science Bowl. Please contact the <a href="mailto:[email protected]">Imaging Platform</a>.</p>
    <p>These images were curated from a variety of sources (below) by the Imaging Platform at the Broad Institute for the 2018 Data Science Bowl. Please contact the <a href="mailto:[email protected]">Imaging Platform</a> with any inquiries.</p>
    <h4>Contributors</h4>
    <ul>
@@ -72,7 +71,7 @@ <h4>Contributors</h4>
        <li>several biologists who wished to remain anonymous</li>
        <li>And of course, the Carpenter lab, Broad Institute</li>
    </ul>
-    
+
 
 
     <h3>Published results using this image set</h3>

Diff for: templates/BBBC039.html

@@ -35,6 +35,7 @@ <h3>Images</h3>
     <p>This data set has a total of 200 fields of view of nuclei captured with fluorescence microscopy using the Hoechst stain. These images are a sample of the larger BBBC022 chemical screen. The images are stored as TIFF files with 520x696 pixels at 16 bits.</p>
     <p><a href="https://github.com/carpenterlab/unet4nuclei">Github repo</a></p>
     <p><a href="images.zip"><i class="icon-download-alt"></i> images.zip (77.9 MB)</a></p>
+    <p>A small fraction of the images in this dataset overlap with the BBBC038 collection, which is the Data Science Bowl 2018 dataset. Not all images in this dataset were included in the DSB 2018 challenge to avoid a dominant number of fluorescent images for the competition. The BBBC038 collection has more variety of experimental conditions, whereas this dataset comes from a single high-throughput experiment with a large number of perturbations.</p>
 
     <h3>Ground truth {{O}}</h3>
     <p>Ground truth annotations are stored as PNG files encoding masks of independent nuclei: if two nuclei touch, they are labeled with a different color. These annotations need to be decoded into labelled matrices to be used as ground truth. Example code for decoding masks can be found in this <a href="https://gist.github.com/jccaicedo/15e811722fca51e3ae90e8b43057f075">gist</a>.</p>

Diff for: templates/BBBC041.html

@@ -36,7 +36,7 @@ <h3>Ground truth {{O}}</h3>
 
     <h3>For more information</h3>
     <p><p>These images were contributed by <a href="mailto:[email protected]">Jane Hung</a> of MIT and the Broad Institute in Cambridge, MA.</p>
-
+    <p>There is also a <a href="https://github.com/tobsecret/Awesome_Malaria_Parasite_Imaging_Datasets">Github reposity</a> that lists malaria parasite imaging datasets (blood smears).</p>
 
     <h3>Published results using this image set</h3>
     <p>These datasets will be evaluated in a publication to be submitted. </p>