Paper
19 January 2001 Texture analysis of tissue structures as a task of nonlinear identification on base of wave-packet decomposition
Dmitriy V. Shutin, Alexander M. Akhmetshin
Author Affiliations +
Abstract
In this work we have developed a new effective method to increase the probity of tissue structure classification based on X-Ray and X-RAY CT images. The proposed method requires much smaller resolution and it is also more sensitive to the small changes in the topology of tissue structure. As initial data, we used X-ray and X-ray CT images of coxa, affected with osteoporosis. The wave packet decompositions of a cut form the image were interpreted as an input and output of virtual non-linear system. The peculiarities of non-linear transfer characteristics were considered for performing a qualitative classification. The method helps to classify about 84% of data visually. A neuron network, which was used for classification based on this technique, has given an opportunity to classify correctly about 94% of all reviewed data. The described method was successfully applied to classification of other tissue.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dmitriy V. Shutin and Alexander M. Akhmetshin "Texture analysis of tissue structures as a task of nonlinear identification on base of wave-packet decomposition", Proc. SPIE 4158, Biomonitoring and Endoscopy Technologies, (19 January 2001); https://doi.org/10.1117/12.413805
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KEYWORDS
X-rays

X-ray imaging

Tissues

X-ray computed tomography

Bone

Diagnostics

Autoregressive models

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