Updated default config, manual, and website. Increased version number to 1.0.2

Author: chinefed

README.md

@@ -80,7 +80,7 @@ For help with DNA2Graph, contact the project maintainer at [federico.chinello@st
 ## Citation
 
 ```text
-F. Chinello, E. Zanella, M. Giannattasio, F. M. Buffa, and Y. Doksani.
+F. Chinello, M. Giannattasio, E. Zanella, F. Bruno, F. M. Buffa, and Y. Doksani.F
 DNA2Graph [Computer software]. Zenodo, 2026.
 https://doi.org/10.5281/zenodo.20413553
 ```

dna2graph/assets/defaults.json

@@ -29,7 +29,7 @@
         "batch_size": 32,
         "min_cycle_length": 100,
         "min_branch_length": 150,
-        "max_thickness": 6,
+        "max_thickness": 20,
         "structurality_depth_cutoff": 50,
         "repair_1_min_graph_distance": 200,
         "repair_1_max_euclidean_distance": 20,

manual/manual.tex

@@ -5,21 +5,21 @@
 \hline
 \textbf{Step} & \textbf{Purpose} \\
 \hline
-Mask-to-Graph Conversion & Convert each segmented DNA molecule in the mask into a spatial graph representation, where nodes correspond to pixels along the molecule with their (x, y) coordinates, and edges encode connectivity. \\
+Mask-to-Graph Conversion & Converts each segmented DNA molecule in the mask into a spatial graph representation, where nodes correspond to pixels along the molecule with their $(x, y)$ coordinates, and edges encode connectivity. \\
 \hline
-Repair Connectivity (1) & Operate on spatial graph representations to address fragmentation caused by segmentation errors in thin DNA structures, by selectively adding edges between relevant node pairs to restore connectivity. \\
+Repair Connectivity (I) & Operates on spatial graph representations to address fragmentation caused by segmentation errors or signal dropout in thin DNA structures, by adding edges between relevant node pairs to restore connectivity. \\
 \hline
-Prune Short Cycles & Operate on spatial graph representations to remove spurious short cycles, using a predefined cycle-length threshold. \\
+Prune Short Cycles & Operates on spatial graph representations to remove spurious short cycles, using a predefined cycle-length threshold. \\
 \hline
-Prune Short Branches & Operate on spatial graph representations to remove spurious short branches, using a predefined branch-length threshold. \\
+Prune Short Branches & Operates on spatial graph representations to remove spurious short branches, using a predefined branch-length threshold. \\
 \hline
-Prune by Thinkness & Clean the spatial graph representations by removing nodes associated with abnormally thick regions, leveraging the prior that DNA structures are thin and thicker regions are typically spurious. \\
+Prune by Thinkness & Cleans the spatial graph representations by removing nodes associated with abnormally thick regions, leveraging the prior that DNA structures are thin and thicker regions are typically spurious. \\
 \hline
-Repair Connectivity (2) & Further refine spatial graph representations by performing a second connectivity repair step, using different parameters from the first repair stage. \\
+Prune Small Components & Discards small spatial graph representations that are likely spurious. \\
 \hline
-Prune Small Components & Discard small spatial graph representations that are likely spurious. \\
+Repair Connectivity (II) & Further refines spatial graph representations by performing a second connectivity repair step, using different parameters from the first repair stage. \\
 \hline
-Graph-to-Mask Conversion & Convert the refined spatial graph representations back into mask form for downstream analysis or visualization. \\
+Graph-to-Mask Conversion & Converts the refined spatial graph representations back into mask form. \\
 \hline
 \end{tabular}
 \label{tab:correction_pipeline}

manual/tables/correction_pipeline.tex

@@ -5,21 +5,21 @@
 \hline
 \textbf{Step} & \textbf{Purpose} \\
 \hline
-Validity mask computation & Compute a binary mask that identifies valid regions of the image, used throughout the pipeline to exclude corrupted or irrelevant areas and prevent them from influencing segmentation. \\
+Validity mask computation & Computes a binary mask that identifies valid regions of the image, used throughout the pipeline to exclude corrupted or irrelevant areas and prevent them from influencing segmentation. \\
 \hline
-Preprocessing & Enhance contrast and standardize intensity distributions to reduce inter-image variability; convert 16-bit images to 8-bit and invert intensities so DNA molecules exhibit higher grayscale values than the background. \\
+Preprocessing & Enhances contrast and standardizes intensity distributions to reduce inter-image variability; converts 16-bit images to 8-bit and inverts intensities so DNA molecules exhibit higher grayscale values than the background. \\
 \hline
-Bilateral Filter & Reduce background noise while preserving edge information, ensuring that thin DNA molecules remain well-defined for subsequent processing. \\
+Bilateral Filter & Reduces background noise while preserving edge information, ensuring that thin DNA molecules remain well-defined for subsequent processing. \\
 \hline
-Unsharp Masking & Enhance edges and local contrast to better highlight DNA structures against the background. \\
+Unsharp Masking & Enhances edges and local contrast to better highlight DNA structures against the background. \\
 \hline
-Hysteresis Thresholding & Generate a binary segmentation by separating DNA molecules from the background. \\
+Hysteresis Thresholding & Generates a binary segmentation by separating DNA molecules from the background. \\
 \hline
-Area-based Pruning (1) & Remove small, spurious segmented regions based on a predefined area threshold. \\
+Area-based Pruning (I) & Removes small, spurious segmented regions based on a predefined area threshold. \\
 \hline
-Morphological Closing & Fill small gaps and discontinuities between segmented regions to improve the structural continuity of DNA molecules. \\
+Morphological Closing & Fills small gaps and discontinuities between segmented regions to improve the structural continuity of DNA molecules. \\
 \hline
-Area-based Pruning (2) & Remove small, spurious segmented regions based on a predefined area threshold, which can differ from the one used in the first pruning stage. \\
+Area-based Pruning (II) & Removes small, spurious segmented regions based on a predefined area threshold, which can differ from the one used in the first pruning stage. \\
 \hline
 \end{tabular}
 \label{tab:segmentation_pipeline}

manual/tables/segmentation_pipeline.tex

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "dna2graph"
-version = "1.0.1"
+version = "1.0.2"
 description = """Imaging software that automates the segmentation and analysis of DNA molecules in electron microscopy images (CLI + GUI)."""
 authors = [
   { name = "Federico Chinello", email = "federico.chinello@studbocconi.it" }

pyproject.toml

@@ -46,12 +46,12 @@ <h2>Installation</h2>
 
           <p>
             This command installs the complete DNA2Graph application, including both
-            the graphical interface and the command-line interface.
+            the graphical user interface and the command-line interface.
           </p>
         </section>
 
         <section>
-          <h2>Launching the Graphical Interface</h2>
+          <h2>Launching the Graphical User Interface (GUI)</h2>
 
           <p>
             After installation, DNA2Graph can be started from a terminal with:
@@ -62,16 +62,16 @@ <h2>Launching the Graphical Interface</h2>
           </div>
 
           <p>
-            This command opens the graphical user interface (GUI).
+            This command opens the graphical user interface.
           </p>
         </section>
 
         <section>
-          <h2>Using the Command-Line Interface</h2>
+          <h2>Using the Command-Line Interface (CLI)</h2>
 
           <p>
             DNA2Graph can also be used directly from the terminal through the
-            command-line interface (CLI):
+            command-line interface:
           </p>
 
           <div class="code-block">

website/download.html

@@ -82,8 +82,7 @@ <h2>What can you do with DNA2Graph?</h2>
           <section id="how-works">
             <h2>How does DNA2Graph work?</h2>
             <p>
-              DNA2Graph offers two alternative approaches for segmentation: a custom, non-learning-based pipeline based on traditional image processing techniques, and a deep learning model trained specifically for this task.
-              In addition, it incorporates novel post-processing algorithms to ensure structural continuity and biological plausibility.
+              DNA2Graph performs an initial segmentation of DNA molecules and subsequently represents each molecule as a spatial graph of nodes and edges. Rather than treating segmentation as a purely pixel-level task, it employs novel graph-based error-correction algorithms to repair segmentation errors and signal interruptions while enforcing biological priors of DNA molecules, such as continuity and thinness.
             </p>
           </section>
 
@@ -110,7 +109,7 @@ <h2>Where can I get help with DNA2Graph?</h2>
             <h2>How to cite DNA2Graph?</h2>
 
             <div class="code-block">
-                <p>F. Chinello, E. Zanella, M. Giannattasio, F. M. Buffa, and Y. Doksani.</p>
+                <p>F. Chinello, M. Giannattasio, E. Zanella, F. Bruno, F. M. Buffa, and Y. Doksani.</p>
                 <p>DNA2Graph [Computer software]. Zenodo, 2026.</p>
                 <p>https://doi.org/10.5281/zenodo.20413553</p>
             </div>

website/index.html

@@ -37,7 +37,7 @@
           <h2>Example Input Image</h2>
 
           <p>
-          We provide the input image used in the GUI and CLI tutorials for download.
+          We provide the input image used in the tutorials for download.
           </p>
 
           <a href="https://github.com/chinefed/DNA2Graph/releases/download/v1.0.1/sample_input.tif" class="btn">Download Example Input Image</a>
@@ -59,8 +59,8 @@ <h2>Getting Started</h2>
           <div class="note-box">
 
         <strong>NOTE:</strong>
-        The trained segmentation pipeline is available as a beta feature.
-        Try the standard pipeline first.
+        The trained segmentation pipeline is a beta feature.
+        The default pipeline is recommended for most users.
         </div>
 
         </section>
@@ -93,12 +93,8 @@ <h2>Advanced Options</h2>
 
         <div class="note-box">
         <strong>NOTE:</strong>
-        The segmenter patch size must not be smaller than the shortest side of the input image.
-        </div>
-        
-        <div class="note-box">
-        <strong>NOTE:</strong>
-        When using the trained segmentation pipeline, the patch size must also be divisible by 32.
+        The segmenter patch size must be smaller than the shortest side of the input image.
+        When using the trained segmentation pipeline, the segmenter patch size must also be divisible by 32.
         </div>
 
       </section>