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Training Data and Models for the paper: Data-efficient U-Net for Segmentation of Carbide Microstructures in SEM Images of Steel Alloys

Chekhonin, Paul; Korten, Till; Gerçek, Alinda Ezgi; Hassan, Maleeha; Steinbach, Peter

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    <dct:title>Training Data and Models for the paper: Data-efficient U-Net for Segmentation of Carbide Microstructures in SEM Images of Steel Alloys</dct:title>
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    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2025</dct:issued>
    <dcat:keyword>machine learning</dcat:keyword>
    <dcat:keyword>SEM</dcat:keyword>
    <dcat:keyword>steel</dcat:keyword>
    <dcat:keyword>carbide</dcat:keyword>
    <dcat:keyword>segmentation</dcat:keyword>
    <dcat:keyword>image processing</dcat:keyword>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2025-11-14</dct:issued>
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    <dct:description>&lt;p&gt;This dataset contains scanning electron microscopy (SEM) images of steel alloys, including paired secondary electron (SE2) and in-lens (InLens) channels, with corresponding binary segmentation labels. The data supports full reproduction of results presented in the referenced manuscript.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Dataset Description&lt;/strong&gt;&lt;/p&gt; &lt;ul&gt; &lt;li&gt;&lt;strong&gt;Content:&lt;/strong&gt;&amp;nbsp;13 pairs of SEM images of two reactor pressure vessel (RPV) steels: &lt;ul&gt; &lt;li&gt;&lt;em&gt;JFL&lt;/em&gt;: IAEA reference RPV base metal steel&lt;/li&gt; &lt;li&gt;&lt;em&gt;ANP-10&lt;/em&gt;: Western type RPV steel&lt;/li&gt; &lt;/ul&gt; &lt;/li&gt; &lt;li&gt;&lt;strong&gt;Acquisition:&lt;/strong&gt; &lt;ul&gt; &lt;li&gt;&lt;em&gt;JFL&lt;/em&gt;: Zeiss NVision 40 microscope&lt;/li&gt; &lt;li&gt;&lt;em&gt;ANP-10&lt;/em&gt;: Zeiss Ultra 55 microscope&lt;/li&gt; &lt;li&gt;Both SE and InLens detectors used simultaneously.&lt;/li&gt; &lt;/ul&gt; &lt;/li&gt; &lt;li&gt;&lt;strong&gt;Resolution:&lt;/strong&gt;&amp;nbsp;2048 &amp;times; 1404 pixels per image &lt;ul&gt; &lt;li&gt;2048 px width corresponds to 14.3 &amp;micro;m (JFL) or 11.5 &amp;micro;m (ANP-10).&lt;/li&gt; &lt;/ul&gt; &lt;/li&gt; &lt;/ul&gt; &lt;p&gt;Using the dataset to reproduce the results of the manuscript&lt;/p&gt; &lt;p&gt;Download the zip file into the&amp;nbsp;&lt;code&gt;data/&lt;/code&gt; subdirectory of the code repository and extract the archive:&lt;/p&gt; &lt;pre&gt;&lt;code class="language-bash"&gt;cd data/ unzip data.zip&lt;/code&gt;&lt;/pre&gt; &lt;p&gt;&lt;strong&gt;Dataset Structure&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;These directories contain the relevant data for the manuscript:&lt;/p&gt; &lt;p&gt;&lt;code&gt;cloud/&lt;/code&gt;&lt;br&gt; &lt;code&gt;├-─ preprocessed/&lt;/code&gt;&lt;br&gt; &lt;code&gt;│ &amp;nbsp; ├── hold-out/&lt;/code&gt;&lt;br&gt; &lt;code&gt;│ &amp;nbsp; ├── images/&lt;/code&gt;&lt;br&gt; &lt;code&gt;│ &amp;nbsp; └── labels/&lt;/code&gt;&lt;br&gt; &lt;code&gt;├── processed_tiles/&lt;/code&gt;&lt;br&gt; &lt;code&gt;│ &amp;nbsp; ├── images/&lt;/code&gt;&lt;br&gt; &lt;code&gt;│ &amp;nbsp; └── labels/&lt;/code&gt;&lt;br&gt; &lt;code&gt;├── tb_logs/&lt;/code&gt;&lt;br&gt; &lt;code&gt;│ &amp;nbsp; ├── unet_model/&lt;/code&gt;&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Preprocessed&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;pre-processed whole images and corresponding labels&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Processed Tiles&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;tiled images and labels&lt;/p&gt; &lt;p&gt;&lt;strong&gt;tb_logs&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;trained model weights&lt;/p&gt;</dct:description>
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Publication date:
November 14, 2025
DOI:
10.14278/rodare.4124

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Keyword(s):
machine learning SEM steel carbide segmentation image processing
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