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Recognition of atherosclerotic plaques and their extended dimensioning with computerized tomography angiography imaging

100%
Markiewicz T., Dziekiewicz M., Maruszyński M., Bogusławska-Walecka R., Kozłowski W.
International Journal of Applied Mathematics and Computer Science
|
2014
|
tom 24
|
nr 1
33-47
EN
In this paper the authors raise the issue of automatic discrimination of atherosclerotic plaques within an artery lumen based on numerical and statistical thresholding of Computerized Tomography Angiographic (CTA) images and their advanced dimensioning as a support for preoperative vessel assessment. For the study, a set of tomograms of the aorta, as well as the ilio-femoral and femoral arteries were examined. In each case a sequence of about 130-480 images of the artery cutoff planes were analyzed prior to their segmentation based on morphological image transformation. A crucial step in the staging of atherosclerotic alteration is recognition of the plaque in the CTA image. To solve this problem, statistical and linear fitting methods, including the least-squares approximation by polynomial and spline polynomial functions, as well as the error fitting function were used. Also, new descriptors of atherosclerotic changes, such as the lumen decrease factor, the circumference occupancy factor, and the convex plaque area factor, are proposed as a means of facilitating preoperative vessel examination. Finally, ways to reduce the computational time are discussed. The proposed methods can be very useful for automatic quantification of atherosclerotic changes visualized by CTA imaging.
2
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An analytical iterative statistical algorithm for image reconstruction from projections

100%
Cierniak R.
International Journal of Applied Mathematics and Computer Science
|
2014
|
tom 24
|
nr 1
7-17
EN
The main purpose of the paper is to present a statistical model-based iterative approach to the problem of image reconstruction from projections. This originally formulated reconstruction algorithm is based on a maximum likelihood method with an objective adjusted to the probability distribution of measured signals obtained from an x-ray computed tomograph with parallel beam geometry. Various forms of objectives are tested. Experimental results show that an objective that is exactly tailored statistically yields the best results, and that the proposed reconstruction algorithm reconstructs an image with better quality than a conventional algorithm with convolution and back-projection.
3
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Assessment of hydrocephalus in children based on digital image processing and analysis

75%
Fabijańska A., Węgliński T., Zakrzewski K., Nowosławska E.
International Journal of Applied Mathematics and Computer Science
|
2014
|
tom 24
|
nr 2
299-312
EN
Hydrocephalus is a pathological condition of the central nervous system which often affects neonates and young children. It manifests itself as an abnormal accumulation of cerebrospinal fluid within the ventricular system of the brain with its subsequent progression. One of the most important diagnostic methods of identifying hydrocephalus is Computer Tomography (CT). The enlarged ventricular system is clearly visible on CT scans. However, the assessment of the disease progress usually relies on the radiologist's judgment and manual measurements, which are subjective, cumbersome and have limited accuracy. Therefore, this paper regards the problem of semi-automatic assessment of hydrocephalus using image processing and analysis algorithms. In particular, automated determination of popular indices of the disease progress is considered. Algorithms for the detection, semi-automatic segmentation and numerical description of the lesion are proposed. Specifically, the disease progress is determined using shape analysis algorithms. Numerical results provided by the introduced methods are presented and compared with those calculated manually by a radiologist and a trained operator. The comparison proves the correctness of the introduced approach.
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