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Research ArticleExperimental Studies
Open Access

Geometric Transformation Algorithm for Acetabular Cup Orientation: Converting 2D Radiographic Projections to 3D Spatial Positioning

GÖKMEN AKTAS, LUKAS HENSLER, SABINE DIPPEL, PIA HEINS, JORGE MAYOR, JAN-DIERK CLAUSEN, EMMANOUIL LIODAKIS, STEPHAN SEHMISCH and TAREK OMAR PACHA
In Vivo May 2026, 40 (3) 1418-1430; DOI: https://doi.org/10.21873/invivo.14293
GÖKMEN AKTAS
1Department of Trauma Surgery, Hannover Medical School, Hannover, Germany;
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  • For correspondence: aktas.goekmen{at}mh-hannover.de
LUKAS HENSLER
2University of Applied Sciences and Arts, Department of Electrical Engineering and Information Technology, Hannover, Germany
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SABINE DIPPEL
2University of Applied Sciences and Arts, Department of Electrical Engineering and Information Technology, Hannover, Germany
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PIA HEINS
2University of Applied Sciences and Arts, Department of Electrical Engineering and Information Technology, Hannover, Germany
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JORGE MAYOR
1Department of Trauma Surgery, Hannover Medical School, Hannover, Germany;
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JAN-DIERK CLAUSEN
1Department of Trauma Surgery, Hannover Medical School, Hannover, Germany;
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EMMANOUIL LIODAKIS
1Department of Trauma Surgery, Hannover Medical School, Hannover, Germany;
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STEPHAN SEHMISCH
1Department of Trauma Surgery, Hannover Medical School, Hannover, Germany;
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TAREK OMAR PACHA
1Department of Trauma Surgery, Hannover Medical School, Hannover, Germany;
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    Figure 1.

    Graphical illustration of a circle in three-dimensional space with elliptical shadow projections onto a horizontal plane.

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    Figure 2.

    Overview of the software-assisted workflow for acetabular cup position measurement, showing the progression from radiograph acquisition through image processing, ellipse detection, and angle calculation. M: Manually performed; SA: semi-automatically performed; A: automatically performed.

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    Figure 3.

    User interface of the software created in Python within the Tkinter package.

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    Figure 4.

    Original image of the pelvic phantom in the Plexiglas device in various planes.

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    Figure 5.

    Interface of the developed program with five points or axis determining the ellipse.

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    Figure 6.

    Illustration of the combined Python classes for automated acetabulum detection and ellipse creation.

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In Vivo: 40 (3)
In Vivo
Vol. 40, Issue 3
May-June 2026
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Geometric Transformation Algorithm for Acetabular Cup Orientation: Converting 2D Radiographic Projections to 3D Spatial Positioning
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Geometric Transformation Algorithm for Acetabular Cup Orientation: Converting 2D Radiographic Projections to 3D Spatial Positioning
GÖKMEN AKTAS, LUKAS HENSLER, SABINE DIPPEL, PIA HEINS, JORGE MAYOR, JAN-DIERK CLAUSEN, EMMANOUIL LIODAKIS, STEPHAN SEHMISCH, TAREK OMAR PACHA
In Vivo May 2026, 40 (3) 1418-1430; DOI: 10.21873/invivo.14293

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Geometric Transformation Algorithm for Acetabular Cup Orientation: Converting 2D Radiographic Projections to 3D Spatial Positioning
GÖKMEN AKTAS, LUKAS HENSLER, SABINE DIPPEL, PIA HEINS, JORGE MAYOR, JAN-DIERK CLAUSEN, EMMANOUIL LIODAKIS, STEPHAN SEHMISCH, TAREK OMAR PACHA
In Vivo May 2026, 40 (3) 1418-1430; DOI: 10.21873/invivo.14293
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