Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
A multi-module enhanced YOLOv8 framework for accurate AO classification of distal radius fractures: SCFAST-YOLO
2
Zitationen
7
Autoren
2025
Jahr
Abstract
Evaluated on our FHSU-DRF dataset (332 cases, 1,456 CT sequences), SCFAST-YOLO achieves 91.8% mAP@0.5 and 87.2% classification accuracy for AO types, surpassing baseline YOLOv8 by 2.1 and 2.3 percentage points respectively. The most significant improvements appear in complex Type C fractures (3.2 percentage points higher classification accuracy) with consistent average recall of 0.85-0.88 across all fracture patterns. The model maintains real-time inference (52.3 FPS) while reducing parameters, making it clinically viable. Extensive qualitative and quantitative results demonstrate the advantages of our approach. Additionally, we show the broader clinical applications of SCFAST-YOLO in enhancing consistency and efficiency in trauma care.
Ähnliche Arbeiten
RADIOGRAPHIC ATLAS OF SKELETAL DEVELOPMENT OF THE HAND AND WRIST
1959 · 5.539 Zit.
Development of an upper extremity outcome measure: The DASH (disabilities of the arm, shoulder, and head)
1996 · 4.941 Zit.
Rating Systems in the Evaluation of Knee Ligament Injuries
1985 · 4.540 Zit.
ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion—Part II: shoulder, elbow, wrist and hand
2004 · 4.411 Zit.
Isolated Hand Paresis: A Case Series
2013 · 4.070 Zit.