Search Results for author:
Found 4 papers, 1 papers with code
FastSAM3D: An Efficient Segment Anything Model for 3D Volumetric Medical Images
Segment anything models (SAMs) are gaining attention for their zero-shot generalization capability in segmenting objects of unseen classes and in unseen domains when properly prompted.
External Attention Assisted Multi-Phase Splenic Vascular Injury Segmentation with Limited Data
The spleen is one of the most commonly injured solid organs in blunt abdominal trauma.
An Interpretable Approach to Automated Severity Scoring in Pelvic Trauma
The method operates similarly to human interpretation of CT scans and first detects distinct pelvic fractures on CT with high specificity using a Faster-RCNN model that are then interpreted using a structural causal model based on clinical best practices to infer an initial Tile grade.
Multi-Scale Attentional Network for Multi-Focal Segmentation of Active Bleed after Pelvic Fractures
Trauma is the worldwide leading cause of death and disability in those younger than 45 years, and pelvic fractures are a major source of morbidity and mortality.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
