Images from CT, MRI, PET, and other medical instrumentation have
become central to the radiotherapy process in the past two decades,
thus requiring medical physicists, clinicians, dosimetrists,
radiation therapists, and trainees to integrate and segment these
images efficiently and accurately in a clinical environment. Image
Processing in Radiation Therapy presents an up-to-date, detailed
treatment of techniques and algorithms for the registration,
segmentation, reconstruction, and evaluation of imaging data. It
describes how these tools are used in radiation planning, treatment
delivery, and outcomes assessment. The book spans deformable
registration, segmentation, and image reconstruction and shows how
to incorporate these practices in radiation therapy. The first
section explores image processing in adaptive radiotherapy, online
monitoring and tracking, dose accumulation, and accuracy
assessment. The second section describes the mathematical approach
to deformable registration. The book presents similarity metrics
used for registration techniques, discussing their effectiveness
and applicability in radiation therapy. It also evaluates
parametric and nonparametric image registration techniques and
their applications in radiation therapy processes. The third
section assesses the efficiency, robustness, and breadth of
application of image segmentation approaches, including
atlas-based, level set, and registration-based techniques. The
fourth section focuses on advanced imaging techniques for
radiotherapy, such as 3D image reconstruction and image
registration using a graphics processor unit. With contributions
from an international group of renowned authors, this book provides
a comprehensive description of image segmentation and registration,
in-room imaging, and advanced reconstruction techniques. Through
many practical examples, it illustrates the clinical rationale and
implementation of the techniques.
General
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