The Rare Disease Achalasia & Digital Innovation: Contrasting Computed Tomography-based & In-house 3D Reconstructions of the Esophagus for Accuracy Assessment

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Main Author: Jochner, David Balint
Format: Recurso digital
Published: Zenodo 2025
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author Jochner, David Balint
author_facet Jochner, David Balint
contents <div> <div> <p>This dataset accompanies the research paper “The Rare Disease Achalasia & Digital Innovation: Contrasting Computed Tomography-based & In-house 3D Reconstructions of the Esophagus for Accuracy Assessment” </p> <p>Included are:</p> <ul> <li> <p>The full PDF of the project report, documenting the methodology and results of validating a multi-modal 3D reconstruction software (EsophagusVisualization) for the esophagus in achalasia patients.</p> </li> <li> <p>Python script for figure generation (<code>Figure_creation.py</code>).</p> </li> <li> <p>Data analysis spreadsheet (<code>Seminar_Ergebnisse.xlsx</code>).</p> </li> <li> <p>3D model files from different steps of the analysis:</p> <ul> <li> <p>CT-based ground truth models (<code>3D-Models_CT.zip</code>)</p> </li> <li> <p>Software reconstructions in different formats (<code>Blender_all_Patients.blend.zip</code>, <code>3D_Slicer_all_Scenes.mrb.zip</code>, <code>3D-Models_SW.zip</code>)</p> </li> <li> <p>CloudCompare input files for quantitative geometric comparison (<code>CloudCompare_Patienten_ALL.bin</code>)</p> </li> </ul> </li> </ul> <p>All files were used in the workflows as described in the manuscript, including segmentation using 3D Slicer, post-processing in Blender, and quantitative validation with CloudCompare.</p> <p>This resource enables full transparency and potential re-analysis of the methods presented in the project.</p> </div> </div>
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institution Zenodo
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publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle The Rare Disease Achalasia & Digital Innovation: Contrasting Computed Tomography-based & In-house 3D Reconstructions of the Esophagus for Accuracy Assessment
Jochner, David Balint
<div> <div> <p>This dataset accompanies the research paper “The Rare Disease Achalasia & Digital Innovation: Contrasting Computed Tomography-based & In-house 3D Reconstructions of the Esophagus for Accuracy Assessment” </p> <p>Included are:</p> <ul> <li> <p>The full PDF of the project report, documenting the methodology and results of validating a multi-modal 3D reconstruction software (EsophagusVisualization) for the esophagus in achalasia patients.</p> </li> <li> <p>Python script for figure generation (<code>Figure_creation.py</code>).</p> </li> <li> <p>Data analysis spreadsheet (<code>Seminar_Ergebnisse.xlsx</code>).</p> </li> <li> <p>3D model files from different steps of the analysis:</p> <ul> <li> <p>CT-based ground truth models (<code>3D-Models_CT.zip</code>)</p> </li> <li> <p>Software reconstructions in different formats (<code>Blender_all_Patients.blend.zip</code>, <code>3D_Slicer_all_Scenes.mrb.zip</code>, <code>3D-Models_SW.zip</code>)</p> </li> <li> <p>CloudCompare input files for quantitative geometric comparison (<code>CloudCompare_Patienten_ALL.bin</code>)</p> </li> </ul> </li> </ul> <p>All files were used in the workflows as described in the manuscript, including segmentation using 3D Slicer, post-processing in Blender, and quantitative validation with CloudCompare.</p> <p>This resource enables full transparency and potential re-analysis of the methods presented in the project.</p> </div> </div>
title The Rare Disease Achalasia & Digital Innovation: Contrasting Computed Tomography-based & In-house 3D Reconstructions of the Esophagus for Accuracy Assessment
url https://doi.org/10.5281/zenodo.16631292