Correspondence free 3D statistical shape model fitting to sparse x-ray projections

Author(s):  
N. Baka ◽  
W. J. Niessen ◽  
B. L. Kaptein ◽  
T. van Walsum ◽  
L. Ferrarini ◽  
...  
Author(s):  
Simant Prakoonwit

A rapid 3D reconstruction of bones and other structures during an operation is an important issue. However, most of existing technologies are not feasible to be implemented in an intraoperative environment. Normally, a 3D reconstruction has to be done by a CT or an MRI pre operation or post operation. Due to some physical constraints, it is not feasible to utilise such machine intraoperatively. A special type of MRI has been developed to overcome the problem. However, all normal surgical tools and instruments cannot be employed. This chapter discusses a possible method to use a small number, e.g. 5, of conventional 2D X-ray images to reconstruct 3D bone and other structures intraoperatively. A statistical shape model is used to fit a set of optimal landmarks vertices, which are automatically created from the 2D images, to reconstruct a full surface. The reconstructed surfaces can then be visualised and manipulated by surgeons or used by surgical robotic systems.


Author(s):  
Simant Prakoonwit

This article discusses a possible method to use a small number, e.g. 5, of conventional 2D X-ray images to reconstruct multiple 3D bone surfaces intraoperatively. Each bone's edge contours in X-ray images are automatically identified. Sparse 3D landmark points of each bone are automatically reconstructed by pairing the 2D X-ray images. The reconstructed landmark point distribution on a surface is approximately optimal covering main characteristics of the surface. A statistical shape model, dense point distribution model (DPDM), is then used to fit the reconstructed optimal landmarks vertices to reconstruct a full surface of each bone separately. The reconstructed surfaces can then be visualised and manipulated by surgeons or used by surgical robotic systems.


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