The international journal of medical robotics + computer assisted surgery : MRCAS · 2025
Measuring Abdominal Skin-Surface Distances Using Photos for Perforator Mapping Analysis-A Validation Study on 3D-Printed DIEP-Flap Models.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Necker Fabian N, Cholok David J, Fischer Marc J, Gifford Kyle, Le Castillo Chris, Scholz Michael, Januszyk Michael, Leuze Christoph W, Daniel Bruce L, Momeni Arash
Аннотация
BACKGROUND: We present a novel method for accurately measuring skin-surface distances using standard smartphone photos and Photoshop, validated on 3D-printed DIEP-flap models and on calibration grid-patterns.
MATERIALS AND METHODS: Distance measurements are acquired in Photoshop in a calibration plane between dots on a grid-pattern as well as between perforators on photos of 3D-printed models and compared against ground-truth. Margins of errors are calculated from fitted linear models.
RESULTS: Submillimeter accuracy can be achieved within errors of ±0.45 mm (80% probability) and ±0.8 mm (95% probability) for measuring distances on the dot-grid. On the 3D-printed DIEP-models, distance measurements are accurate within ±1.75 mm (80% probability) and ±3.1 mm (95% probability).
CONCLUSIONS: We introduce a simple yet highly accurate technique to measure skin-surface distances using normal photos. Depending on the scenario, submillimeter or conservatively very low millimetre errors can be achieved, sufficiently accurate for clinical use, whilst maintaining topographic relationships of the measurements.
MATERIALS AND METHODS: Distance measurements are acquired in Photoshop in a calibration plane between dots on a grid-pattern as well as between perforators on photos of 3D-printed models and compared against ground-truth. Margins of errors are calculated from fitted linear models.
RESULTS: Submillimeter accuracy can be achieved within errors of ±0.45 mm (80% probability) and ±0.8 mm (95% probability) for measuring distances on the dot-grid. On the 3D-printed DIEP-models, distance measurements are accurate within ±1.75 mm (80% probability) and ±3.1 mm (95% probability).
CONCLUSIONS: We introduce a simple yet highly accurate technique to measure skin-surface distances using normal photos. Depending on the scenario, submillimeter or conservatively very low millimetre errors can be achieved, sufficiently accurate for clinical use, whilst maintaining topographic relationships of the measurements.