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Perfusion CT with its capability to display various cerebral perfusion parame-
ters not only allows the registration of collateral blood supply, but also permits a
quantitative evaluation of the degree of severity of the perfusion disturbance
which results from the particular type of occlusion and collateral blood supply
[13]. In the process of analysis PCT maps neuroradiologist detect, measure and
describe the asymmetry between perfusion in left and right hemisphere of the
patient.
Commercial software for perfusion imaging that is broadly applied in hospitals
does not feature any mechanisms or modules that would facilitate the automatic
detection of perfusion anomalies or is capable to detect only certain type of them.
Brilliance Workspace for CT by Philips has special "Brain Perfusion" module that
offers so called Summary Maps [41]. This software utilizes well known algorithm
proposed in [36]. It was reported that algorithm enables to distinguish the penum-
bra from infarcted tissue in acute stroke patients. Ischemic tissue (infarct plus
penumbra) was defined as cerebral pixels with a decrease of more than 34% in ce-
rebral blood flow compared with that in clinically normal areas in the cerebral
hemispheres. A cerebral blood volume threshold of 2.5 ml/100 g was selected
within the ischemic area, and higher and lower values were considered to
represent the penumbra and the infarct, respectively. The usage of that method
was reported in
[33]
[20]
.
The CAD system described in [23] enables detection of potential stroke regions
in 3D MR scans of patient's head so it is mainly limited for MR images. These 3D
scans are used for atlas-to-image registration (with the brain anatomy atlas - AA)
in order to perform labeling of brain structures. The Fast Talairach Transform
(FTT) for Magnetic Resonance Neuroimages is used [24]. FFT was developed on-
ly for 3D Magnetic Resonance (MR) images and it is based on detection some
”key points” of the brain structure (structural - based registration [32]) that are lat-
terly used for rigid transformation of brain templates. In [3] the authors presents a
tool especially designed for the PWI-DWI data processing that integrates registra-
tion, segmentation, manipulation and visualization techniques. At first, the au-
thors integrate DWI and PWI data in a common coordinate system by applying a
registration technique. Second DWI data is processed to identify and measure the
infarct area (a semi-automatic segmentation technique based on thresholding).
Third, by using the information of the previous steps, PWI data is processed to
identify the lesion. Due to the difficulty of processing PWI data segmentation
process is supervised by the radiologist.
The researches in the field of computer - assisted analysis of ischemic stroke
are also conducted by other Polish research groups [25], [27], [26]. In [25] para-
digm of stroke monitor aimed to make visible acute ischemic signs in unenhanced
CT brain imaging is presented. Three-staged algorithm is based on soft tissue ex-
traction and segmentation of stroke-susceptible regions, multiscale image
processing with noise/artifacts reduction and local contrast enhancement followed
by adaptive visualization of extracted structures. The Ischemic stroke monitor has
flexible interface with possible extensions to manage examination protocol. The
experimental verification confirmed usefulness of stroke monitor for educational
and acute diagnosis purposes. Stroke slicer [26] is computer aided diagnosis tool
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