A data-driven approach for assembling intertrochanteric fractures by axis-position alignment

In clinics, the reduction of femoral intertrochanteric fractures should meet the medical demands of both axis alignment and position alignment. State-of-the-art approaches are designed for merely position alignment, not allowing for axis alignment. The axis-position alignment can be formulated as a...

Full description

Saved in:
Bibliographic Details
Published in:IEEE access 2020-01, Vol.8, p.1-1
Main Authors: Deng, Ziyue, Jiang, Junfeng, Liu, HongWei, Chen, Zhengming, Huang, Rui, Zhang, Wenxi, He, Kunjin
Format: Article
Language:English
Subjects:
3D model
Algorithms
Alignment
Artificial neural networks
Assembling
axis-position alignment
Bones
Constraints
data-driven
fracture reduction
Fractures
intertrochanteric fracture
Iterative methods
Optimization
Orthopedics
Semantics
Shafts
Shape
Surface cracks
Three-dimensional displays
Training
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In clinics, the reduction of femoral intertrochanteric fractures should meet the medical demands of both axis alignment and position alignment. State-of-the-art approaches are designed for merely position alignment, not allowing for axis alignment. The axis-position alignment can be formulated as a least square optimization problem with the inequality constraints. The main challenges include how to solve this constrained optimization problem and effectively extract the semantic of the randomly fractured bone pieces. To address these problems, a semi-automatic data-driven method is introduced. First, the medical semantic parameters are computed, at the beginning of when the 3D input pieces' anatomical areas are labeled by using the deep neural network. A statistical shape model is leveraged to generate the synthetic training data so as to learn the anatomical landmarks of the pieces, greatly reducing the labeling costs for training. The final reduction position of the pieces is obtained through iterative axis alignment and position alignment. Our method is evaluated by three baselines, i.e., the manual assembly of the orthopaedic specialists and two typical bone assembling methods. The presented method solves an optimization problem for assembling intertrochanteric fracture by axis-position alignment. All cases can be successfully assembled with the developed algorithm which is proved to be capable of reaching the clinical demand.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3012047