A Novel Deep Hybrid Model for Automatic Femoral Stem Classification in Hip Arthroplasty From Radiographs: MSFT-Net With CBAM and Transformer Modules

A Novel Deep Hybrid Model for Automatic Femoral Stem Classification in Hip Arthroplasty From Radiographs: MSFT-Net With CBAM and Transformer Modules

Accurate identification of femoral stem implants in hip arthroplasty is essential for effective revision surgery, minimizing operative complexity, patient morbidity, intraoperative blood loss, and postoperative recovery time. In cases where prior implant data are unavailable, manual identification i...

Full description

Saved in:
Bibliographic Details
Main Authors: Emre Gogus, Atinc Yilmaz, Meric Enercan
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
CBAM attention mechanism
deep learning
femoral stem classification
hip implant
hip arthroplasty
multi-scale feature fusion
Online Access:https://ieeexplore.ieee.org/document/11030603/
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items