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Skull Reconstruction Using Statistical Shape Models

Rosendal, Patrik LU (2020) In Master's Theses in Mathematical Sciences FMAM05 20201
Mathematics (Faculty of Engineering)
Abstract
In case of a head injury or trauma a surgeon opens up the skull by removing a bone piece of the skull to either relieve pressure or get access to brain
tissue. The first option is to follow up with putting back the same skull
piece. In the circumstances this is not possible however, a surgeon must
open up the skull and form a piece using bone cement that fits the whole
during the surgery, which is time consuming This leads to an increase risk
of infection and other medical risks for the patient.
This project investigates the possibility to mathematically reconstruct
the piece missing in the skull, giving the surgeon the option to already
have a fitted piece ready before the operation begins.
The goal of the project was to... (More)
In case of a head injury or trauma a surgeon opens up the skull by removing a bone piece of the skull to either relieve pressure or get access to brain
tissue. The first option is to follow up with putting back the same skull
piece. In the circumstances this is not possible however, a surgeon must
open up the skull and form a piece using bone cement that fits the whole
during the surgery, which is time consuming This leads to an increase risk
of infection and other medical risks for the patient.
This project investigates the possibility to mathematically reconstruct
the piece missing in the skull, giving the surgeon the option to already
have a fitted piece ready before the operation begins.
The goal of the project was to investigate if a statistical shape model
could be used for cranial reconstruction. The model was built from a
data set from Skåane University Hospital, it was preprocessed using Medviso Segment 3D Print software and all other implementation was done
in Matlab. Each skull were sampled to a point cloud, with skull radii and
thickness as parameters. The shape model was built from a point cloud
sampled from each skull. The skulls were registered to each other using
ICP registration. The resulting model reconstruct successfully a damaged
skull with 1 mm average error. Six modes were enough to account for
90% of the shape variability. The results of average error of 1 mm was
not deemed enough to be clinically useful. (Less)
Please use this url to cite or link to this publication:
author
Rosendal, Patrik LU
supervisor
organization
alternative title
Skallrekonstruktion
course
FMAM05 20201
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Skull Reconstruction, PCA, ICP Registration
publication/series
Master's Theses in Mathematical Sciences
report number
2020:E37
ISSN
1404-6342
other publication id
LUTFMA-3417-2020
language
English
id
9031739
date added to LUP
2020-12-14 19:24:01
date last changed
2020-12-14 19:24:01
@misc{9031739,
  abstract     = {{In case of a head injury or trauma a surgeon opens up the skull by removing a bone piece of the skull to either relieve pressure or get access to brain
tissue. The first option is to follow up with putting back the same skull
piece. In the circumstances this is not possible however, a surgeon must
open up the skull and form a piece using bone cement that fits the whole
during the surgery, which is time consuming This leads to an increase risk
of infection and other medical risks for the patient.
This project investigates the possibility to mathematically reconstruct
the piece missing in the skull, giving the surgeon the option to already
have a fitted piece ready before the operation begins.
The goal of the project was to investigate if a statistical shape model
could be used for cranial reconstruction. The model was built from a
data set from Skåane University Hospital, it was preprocessed using Medviso Segment 3D Print software and all other implementation was done
in Matlab. Each skull were sampled to a point cloud, with skull radii and
thickness as parameters. The shape model was built from a point cloud
sampled from each skull. The skulls were registered to each other using
ICP registration. The resulting model reconstruct successfully a damaged
skull with 1 mm average error. Six modes were enough to account for
90% of the shape variability. The results of average error of 1 mm was
not deemed enough to be clinically useful.}},
  author       = {{Rosendal, Patrik}},
  issn         = {{1404-6342}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{Master's Theses in Mathematical Sciences}},
  title        = {{Skull Reconstruction Using Statistical Shape Models}},
  year         = {{2020}},
}