FRACTAL SLOPE DETERMINATION OF IMAGES WITH NOISE REDUCTION THROUGH WAVELET TRANSFORMATION OF SAMPLES OF RED BLOOD CELL POPULATIONS WITH DIFFERENT PATHOLOGIES

ANDRÉS MARTÍNEZ BILESIO; BORTOLATO, SANTIAGO A.; MARIANA RAVIOLA; ANA KOROL; MANCILLA CANALES MANUEL; PATRICIA PONCE DE LEÓN

Santa Fe

Congreso; XXIV Congreso sobre Métodos Numéricos y sus Aplicaciones; 2019

In hemorheology is desirable to develop and to complement existing traditional analytical methods in order to diagnose different pathologies that could relate with the dynamic hemoreological properties of the constituents of blood. Fractal dimension is a useful tool for the characterization of different red blood cells (RBCs) populations and their interactions because the determination of this dimension in the images depends on the morphology of the erythrocytes and on the aggregates in which they participate. In the present work it was propose to characterize images of RBC obtained from conventional optical microscopy. The RBCs were obtained from patients with β-thalassemia heterozygous (βTh-H), patients affected with parasites (trichinosis and ascariasis), leukemia, ferric deprived anemic patients and also healthy donors, which were used as controls. The digital images of the samples were acquired with a Mikova DCM500 digital camera incorporated on an optical microscope (objective: 40X). Noise elimination was performed with the application of wavelet transform on the images (through decomposition of the signal in a collection of wavelet signals and the selection of the more significant ones in order to reconstruct the original signal), then Fractal Dimension values were estimated through the Box-Counting Dimension. The samples of patients with parasitism and acute leukemia showed significant differences in their variance (Levene Test, p