Information Technology Reference
In-Depth Information
and on the research activity and clinical environment that stimulate image formation
and its application. Image formation can be de
ned as the process of mapping selected
properties of the imaged object into the image space. The image space represents the
basis for visualization of the object and its properties, and may be further used
for quantitative evaluation of its structure or function, and interpretation of the
information it contains. As quantitative evaluation and interpretation of images
depend on the quality of the information of interest, the main purpose of image
visualization is effective information extraction. In the
field of medical image visu-
alization, the extraction of clinically relevant information is therefore of signi
cant
importance for the development of accurate and non-invasive techniques for medical
diagnosis and treatment.
Technological advances in medical imaging and computerized medical image
processing led to the development of new three-dimensional (3D) image acquisition
techniques that have become important clinical tools in modern diagnostic radiol-
ogy and medical health care. Two-dimensional (2D) images, especially radiographs
(X-ray images), are still widely present in clinical examination due to a relatively
low acquisition price and wide area of application. However, the continuous
increase in the number of acquired cross-sections, reduction in cross-sectional
thickness and relatively short acquisition times led to the expansion of 3D imaging
techniques [
70
]. Among the most important 3D techniques are computed tomog-
raphy (CT) and magnetic resonance (MR) imaging, which provide qualitative data
of the imaged structures. However, characteristic features of these techniques and
variable positioning of the patient during image acquisition still represent a major
source of variability that causes errors in the interpretation of image information.
On the other hand, human capability of discovering and diagnosing diseases by
proper interpretation of medical images is limited due to our non-systematic search
patterns. Moreover, the presence of noise may conceal the natural anatomical
background, such as actual geometrical relationships among anatomical structures,
which may further hamper mental reconstruction of the 3D image information.
Errors in interpretation may also be caused by similar characteristics of normal and
pathological conditions, and by the natural biological variability of human anatomy.
Image interpretation and quantitative evaluation therefore to a great extent depend
on adequate visualization of the information about anatomical structures. As the
information of interest is often associated with characteristic features of the selected
structure or process, it is crucial to use specially designed image processing tech-
niques for visualization and quantitative evaluation. As the number of acquired
medical images is rapidly growing [
7
], computerized tools and devices may
potentially help radiologists to reduce their workloads [
73
,
77
] and direct clinicians
towards an accurate interpretation and quantitative evaluation of the large amount
of data within a reasonable time frame [
75
,
76
]. Techniques for visualization and
quantitative evaluation of medical images are therefore extremely valuable in the
development of image-assisted diagnosis, planning of surgical interventions and
assessment of medical treatment outcomes.
Both CT and MR are established image acquisition techniques for diagnosing
and managing spinal and spine-related disorders [
12
,
81
], as they provide
