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X-Ray Tomography Crystal Characterization: Automatic 3D Segmentation.

Gautier Hypolite1, Jérôme Vicente2, Philippe Moulin1

  • 1Equipe Procédés Membranaires (EPM), Aix Marseille Univ., CNRS, Centrale Marseille, (M2P2 UMR 7340), Equipe Procédés Membranaires (EPM), Europôle de l'Arbois, BP80, Pavillon Laennec, Hall C, France.

Microscopy and Microanalysis : the Official Journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
|September 25, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a new 3D crystal imaging method using micro X-ray computed tomography. The novel approach significantly improves crystal segmentation accuracy, reducing oversegmentation by 87% compared to traditional watershed methods.

Keywords:
SegmentationX-ray tomographycrystallisationsurface recognation

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Area of Science:

  • Crystallography
  • Materials Science
  • Image Analysis

Background:

  • Accurate crystal structural parameter analysis is crucial for pharmaceutical and chemical industries.
  • Existing crystal segmentation methods, like watershed, often suffer from oversegmentation.
  • Micro X-ray computed tomography (micro-CT) provides detailed 3D crystal imaging.

Purpose of the Study:

  • To develop and evaluate a novel crystal segmentation method for 3D micro-CT images.
  • To improve segmentation accuracy over conventional watershed techniques.
  • To enable more precise analysis of crystal structural parameters.

Main Methods:

  • A new segmentation method based on surface plane recognition was developed.
  • The method was applied to 3D crystal images obtained via micro X-ray computed tomography.
  • Segmentation performance was evaluated using synthetic images and real crystal samples (potassium alum, chromium alum, copper sulfate).

Main Results:

  • The proposed method significantly reduced oversegmentation by 87% compared to watershed with ultimate erosion.
  • The algorithm maintained the convexity of the recognized crystal particles.
  • Successful application demonstrated on diverse crystalline samples.

Conclusions:

  • The novel plane recognition-based segmentation method offers superior performance for 3D crystal imaging.
  • This advancement facilitates more accurate structural analysis in crystal growth studies.
  • The method holds potential for enhanced quality control and research in chemical and pharmaceutical fields.