A fractal mathematics smoothing method for selective diagnosis of damaged erythrocytes

PATRICIA PONCE DE LEÓN; BORTOLATO, SANTIAGO; MANCILLA CANALES MANUEL; ANA M. KOROL

Córdoba

Congreso; II Brazil-Argentine Microfluidics Congress. V Congreso de Microfluídica Argentina October 22-; 2019

UNC

Automatic characterization of different populations of red blood cells (RBCs) is a usefultool in Hematology and Clinical Diagnosis. In this work we focus on different pathologiesthat affect hemorheological properties of humans being blood. Our main aim is to developan analytical methodology to aid in the diagnosis of those pathologies that undergospecifically by altering RBCs membrane dynamic properties. The alterations on the RBCmembranes were studied with box-counting dimension (BCD). BCDs were estimated bya standardized analysis of denoised images of RBC suspensions obtained with an opticalmicroscope and a non-professional digital camera. The systematical denoising was carriedout by application of Wavelet Transform on the images. BCD is a fractal quantifier thathas been proven to depend on the levels of RBC aggregation. Wavelet Transform denoisingtechnique implies the decomposition of the image signals in a set of wavelets and theselection of the most significant ones through which the image can be reconstructed. Inthis work we compared the BCD estimated on RBC suspensions from healthy individualsand from those affected by parasitosis (trichinosis and ascariasis), leukemia (chronic andacute) and iron-deficiency anemia. In comparison to control samples, those correspondingto patients with parasitosis and acute leukemia showed significative differences (p