Using of Color Model and Contrast Variation in Wavelet Ideology for Study <i>Megaloblastic Anemia Cells</i>

Abstract

Processing and analyzing of medical images is one of the priority research areas. At the same time, the processing of images of cells occupies a special place. This is due to the fact that such studies allow for a comprehensive diagnosis of the state of human health, identify and prevent the development of diseases in the early stages. We investigate the effectiveness of using wavelet analysis in color models, taking into account the preliminary change in the contrast of the input image. We consider the HSV color model and the image contrast modification procedure, which is based on the histogram change in the specified range with gamma correction. As a criterion for choosing parameters for changing the contrast of the image, we consider the entropy of the image. We also showed the advisability of using the value of the entropy index for the subsequent improvement of image analysis based on the wavelet ideology. We examined the general sequence of action for the analysis of image of megaloblastic anemia cells. This sequence is based on the choice of parameters for changing the contrast of the image and application of wavelet ideology.

Identification of Megaloblastic Anemia Cells Through the Use of Image Processing Techniques

“…In this way most systems for medical images recording and analyzing work [9]. But for analysis we can use other systems of color image, for example, it can be HSV color system: channels-H (hue), S (saturation), V (volume or brightness) [12]. Such a transition allows us to emphasize the features of the cellular structure because of the difference in perception and representation of the image points for different color spaces.…”

“…We apply the method of histogram change in the specified range with gamma correction. We conducted studies that showed that the histogram change in the specified range with gamma correction combined with the conversion of color space from RGB to HSV increases the contrast of the original image by an order in comparison with other methods [12]. This result is associated with emphasizing the low contrast areas of the original image due to non-linear transformation of the original image (color space modification) and subsequent non-linear correction of the converted image.…”

“…This wavelet function allows us to select the outline of all original image elements. The wavelet analysis procedure is described in detail by Lyashenko et al [1,8,12], Kobylin and Lyashenko [11].…”

“…If we process image, then the threshold level will also change. Therefore, to improve image quality, we suggest using the method histogram change in the specified range with gamma correction [12]. This allows us to get a good level of contrast for the image and make the details of our image clearer.…”

“…For segmentation we use the ideology of wavelet analysis [12]. This avoids the errors that arise in the case of classical segmentation.…”