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Chapter 10

MEDRADSC 2Z03 Chapter Notes - Chapter 10: Grayscale, Data Acquisition

Medical Radiation Sciences
Course Code
Dawn Danko

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Treatment Planning
To estimate the parameters of the coordinate transformation that relates
homologous points in the two studies
To apply the resultant transformation to map structures or features of interest
from one study to another
A. Dataset registration
Measure the degree of mismatch, use standard numberical methods to
determine the transformation parameters that minimize the metric
Two algorithms
1. Surface-based registration
Surfaces of one or more anatomic structures are extracted from the image data
and used for comuting and minimizing the mismatch between the datasets
Common: skull for brain, pelvis for prostate
1. Image-based registration
Grayscale data is used directly to compute a measure of mismatch or similarity
between two datasets
--> much less pre-processing of the data
Mutual information based metric
oA measure of how much redundant information is present between the
pair of datasets
1. Interactive techniques
Numerical approaches
Some form of visual feedback and appropriate widgets to manipulate and
register two datasets
Effective in cases when transformation can be represented by a small number of
degrees of freedom e.g. only rotations, translations, isotropic scling
A. Structure Mapping and Image fusion
Data is integrated or fused with that of another
1. Structure mapping
Produces outlines of structures
1. Construct a 3-D approximation from 2-D outlines
Accomplished by tiling outlines in adj images, capping the top and bottom
outlines to creat a closed surfaces
1. Image mapping and fusion
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