Data

AutoSeg Evaluator

The University of Western Australia
Rusanov, Branimir
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.5281/zenodo.17383137&rft.title=AutoSeg Evaluator&rft.identifier=10.5281/zenodo.17383137&rft.publisher=Zenodo&rft.description=AutoSeg Evaluator reduces the technical and resource barriers required to conduct large-scale segmentation quality evaluations. The tool is freely offered to expedite the assessment and implementation of AI-based autocontouring systems, while also being a useful tool in the pocket of researchers that routinely investigate segmentation quality. AutoSeg Evaluator:  • Allows clinicians to overcome the technical expertise barrier required for converting RTSS DICOM files and evaluating segmentations by packaging all functionality within an executable graphical user interface (GUI). • Provides users with a choice of common and advanced metrics using validated open-source implementations. Metrics include volumetric Dice Coefficient, Hausdorff Distance (95th and 100th percentile), Mean Surface Distance, Added Path Length (APL), and Surface Dice. • Supports visualization functionality allowing users to verify outliers and perform sanity checks. • Efficiently handles batched analyses with minimal user interaction by automatically detecting similarly named structures across patients and RTSS files using a template matching feature. Custom string replacement rules enable standardised structure renaming, improving string-matching efficiency.  • Computational queues can be set to run in the background across multiple patients and structures while the user prepares the next batch of data. • Outputs detailed results logs for statistical evaluation. &rft.creator=Rusanov, Branimir &rft.date=2025&rft.type=dataset&rft.language=English Access the data

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AutoSeg Evaluator reduces the technical and resource barriers required to conduct large-scale segmentation quality evaluations. The tool is freely offered to expedite the assessment and implementation of AI-based autocontouring systems, while also being a useful tool in the pocket of researchers that routinely investigate segmentation quality. AutoSeg Evaluator:  • Allows clinicians to overcome the technical expertise barrier required for converting RTSS DICOM files and evaluating segmentations by packaging all functionality within an executable graphical user interface (GUI). • Provides users with a choice of common and advanced metrics using validated open-source implementations. Metrics include volumetric Dice Coefficient, Hausdorff Distance (95th and 100th percentile), Mean Surface Distance, Added Path Length (APL), and Surface Dice. • Supports visualization functionality allowing users to verify outliers and perform sanity checks. • Efficiently handles batched analyses with minimal user interaction by automatically detecting similarly named structures across patients and RTSS files using a template matching feature. Custom string replacement rules enable standardised structure renaming, improving string-matching efficiency.  • Computational queues can be set to run in the background across multiple patients and structures while the user prepares the next batch of data. • Outputs detailed results logs for statistical evaluation. 

Notes

External Organisations
Sir Charles Gairdner Hospital
Associated Persons
Branimir Rusanov (Creator)

Issued: 2025-10-18

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Identifiers
ACN 633 798 857