Medical imaging plays a key role in treatment of various cancer types and in particular in
image-guided radiotherapy (IGRT) and can be used in all stages of the radiotherapy treatment
including accurate target delineation and radiation dose calculations in the planning
of IGRT. Magnetic resonance (MR) imaging is often used for accurate soft-tissue delineation
and computed tomography (CT) images are used for radiation dose calculations.
The accurate target delineation together with multimodal imaging may enable a smaller
radiation field. This is important in IGRT as it enables a high radiation dose to the target
and minimizes the radiation dose to the surrounding healthy tissue, which results in an
improved treatment outcome with lower toxicity and reduced side-effects.
The use of multimodal imaging requires alignment of MR and CT in order to map
the target delineation in MR to CT for dose calculations. The target delineation and the
image alignment are today widely performed manually and are therefore time-consuming,
labor-intensive, and prone to observer variations. The target for radiation is extended to
include healthy tissue to ensure that the tumor is always radiated during treatment as a
consequence of the observer variation together with other uncertainties.
The thesis seeks to address these challenges in the planning of radiotherapy of prostate
cancer. Prostate cancer is a cancer type where the treatment highly benefits from the use
of IGRT and multimodal imaging. The prostate is delineated as the target in MR because
of the good soft-tissue visualization in MR and a following image alignment enables dose
calculations based on CT. At Aalborg University Hospital a newly developed removable
Ni-Ti prostate stent is implanted into the prostate gland and is used as a fiducial marker
to achieve an accurate alignment of the prostate in MR and CT. The first part of the
thesis focuses on automatic image alignment using voxel similarity and on a comparison
of the automatic approach with the current clinical approach. The second part focuses
on automatic target delineation. Two automatic approaches for target delineation in MR
using both voxel intensities and knowledge about the shape are developed and validated.
The approaches presented are expected be adaptable to target delineation and image
alignment of other soft-tissue organs.
Image Registration and Image
Segmentation for Image-
Guided Radiotherapy of