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|Title:||Contour detection and allocation for cytological images using Wavelet analysis methodology|
|Citation:||Lyashenko V. Contour detection and allocation for cytological images using Wavelet analysis methodology / V. Lyashenko, R. Matarneh, O. Kobylin, Y. Putyatin // International Journal of Advance Research in Computer Science and Management Studies. – 2016. – Vol. 4, Iss. 1. – P. 85–94.|
|Abstract:||Image analysis is one of most powerful tools in various research fields. In the same context, processing of microscopic images in medicine has high priority research area, this is because such studies allow conducting comprehensive diagnosis of human health state, identifying and preventing the development of diseases in the early stages and providing additional research in non-standard symptomatic forms of rare diseases. To overcome analyzing and processing complexities of microscopic images the feasibility of using wavelet analysis methodology had been considered with a high attention to the effect of wavelet transform scaling which is used to detect contours of objects in the image. The new approach showed that the effectiveness of contour detection is largely depends on wavelet transform scaling to identify gaps in the wavelet decomposition of the investigated images.|
|Appears in Collections:||Кафедра інформатики (ІНФ)|
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