Evidence map›Paper›PMID 41942388›Full record

ArticleActa orthopaedica et traumatologica turcica2026

Evaluation of the reliability of novel pelvic X-ray assessment software: CalculOrther.

Abdurrahman Yılmaz, Turab Selçuk, Taha Aksoy, Bülent Atilla

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Article in Acta orthopaedica et traumatologica turcica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Abdurrahman YılmazDepartment of Orthopaedics and Traumatology, Hacettepe University Faculty of Medicine, Ankara, Türkiye.
Turab SelçukDepartment of Electrical & Electronics Engineering, Kahramanmaraş Sütçü İmam University, Türkiye.
Taha AksoyUniversity of Miami, Florida, United States.
Bülent AtillaDepartment of Orthopaedics and Traumatology, Hacettepe University Faculty of Medicine, Ankara, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe anteroposterior (AP) pelvic X-ray is commonly used for assessing conditions affecting the bony pelvis. The objective of this study was to develop new pelvic X-ray assessment software (CalculOrther) to assess AP pelvic X-rays and evaluate its reliability.  Methods: CalculOrther was developed in 4 stages. Initially, a dataset comprising pelvic X-rays was generated. During the second stage, the convolutional neural network model was trained to identify anatomical landmarks in the pelvic X-ray images. The Hough transform was used to locate the circle and center of the femoral head in the third stage. The border pixels were generated using mathematical morphological processes, and the requisite angles were measured in the fourth stage. Then manual measurements and the software developed were analyzed with Pearson's correlation and intraobserver and interobserver correlation coefficients. Subsequently, the mean error and the root mean square error (RMSE) were acquired.  Results: The Pearson's correlation coefficients varied from 0.84 to 0.99 (P < .001). The interobserver and intraobserver correlation coefficients ranged from 0.77 to 0.99 and from 0.75 to 0.94, respectively. The RMSE ranged from 0.31 to 4.38 and the mean error from 0.05 to 2.86. The mean duration for manual measurements was 230 (177-284) seconds and 215 (160-255) seconds, respectively. The software required an average time of 3.18 (2.95-3.52) seconds to make the same measurements.  Conclusion: Regarding femoroacetabular impingement and hip dysplasia, artificial intelligence can analyze pelvic radiographs and generate equally accurate results within a shorter duration compared to traditional measuring methods.      Cite this article as: Yilmaz A, Selcuk T, Aksoy T, Atilla B. Evaluation of the reliability of novel pelvic X-ray assessment software: CalculOrther. Acta Orthop Traumatol Turc., 2026; 60(1), 0268, doi: 10.5152/j.aott.2026.25268.

Indexed as

Pelvic BonesPelvisRadiographic Image Interpretation, Computer-AssistedRadiographySoftwareConvolutional Neural NetworksHumansObserver VariationReproducibility of Results

Identifiers

PMID41942388
PMCPMC13051582

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.