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ABSTRACT: Background
Accurate segmentation of rib fractures represents a pivotal procedure within surgical interventions. This meticulous process not only mitigates the likelihood of postoperative complications but also facilitates expedited patient recuperation. However, rib fractures in computed tomography (CT) images exhibit an uneven morphology and are not fixed in position, posing difficulties in segmenting fractures. This study aims to enhance the accuracy of elongated rib fracture segmentation, ultimately improving the efficiency of clinical diagnosis.Methods
In this study, we propose multi-stream and multi-scale fusion network based on efficient attention UXNet (M2SUXNet). It aims to enhance the segmentation accuracy of elongated rib fractures through multi-scale fusion atten
SUBMITTER: Liu Y
PROVIDER: S-EPMC11744184 | biostudies-literature | 2025 Jan
REPOSITORIES: biostudies-literature