Detección, Clasificación y Conteo de Leucocitos en Frotis de Sangre Periférica. J . Martínez-Castro* S. Reyes-Cadena** E. Felipe-Riverón *. * Centro de. Scribd is the world’s largest social reading and publishing site. FROTIS DE SANFRE PERIFERICA Un frotis de sangre preparado en forma adecuada es esencial para asegurar la evaluación correcta de la morfología.

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Fortunately, the science of electronics and computing has moved closer to other branches of knowledge, as it is the case of the hematology, in order to support and provide solutions to the problems they face.

Anemias of Chronic disease, peripheral blood smear [Internet]. More recently Ghosh et al. The effectiveness of our method was tested with a blind experiment.

Frotis de sangre

Table 4shows the classification of the results obtained for each type of leukocytes based on sanngre equations Table 5 shows the values achieved with the common equations related to the confusion matrix. Discriminatory analysis, nonparametric periderica With this, we obtained an image with the objects of interest more defined nucleiFig. Color Atlas of Clinical Hematology. Despite its simplicity, it offers very good performance on many problems. Then, we described the methodologies carried out in the segmentation of each type of leukocyte.

White perigerica cells are classified into five main groups: Generalmente existen varias causas de anemia en el anciano. Swar m an d Evolutionar y Computation11 0: NCI; [citado 21 Abr ]. For this reason, we calculated the area of objects counting the pixels of each object. Next, we included an analysis of the antecedents and the state of the art.

Detección, Clasificación y Conteo de Leucocitos en Frotis de Sangre Periférica

The point 0, 1 represents the perfect classification. The tincture most frequently employed for dying leukocytes is called Wright and Giemsa. Hitherto, automatic cell classification systems cannot meet yet the complexity of real clinical demands. Rev Hosp Ital B Aires. Frotis de sangre [Internet]. Examination of peripheral blood films using automated microscopy; evaluation of diffmaster octavia and cellavision dm In order to validate segmentation output it is necessary to know the ground truth that is the true features of each object of interest.


It is important to emphasize that this work does not attempt to diferentiate between smears of leukocytes coming from healthy and sick people; this is because most frofis produce a change in the differential count of leukocytes rather than in theirs forms.

Automatic classifier of leukocytes, k -NN, Minkowski metric, Pattern recognition, Digital image processing. Once the cells are fully segmented, the classifier k -NN was applied using the first Minkowski metric 1 to perform the count of the five normal shapes objects of study.

Then, the processes for the reduction of the additive noise and the frois improvement are carried out.


We know a priori five classes, namely, the five types of leukocytes to ve classified: These solutions are built, in its majority, based on the introduction of mathematical methods, algorithms and software tools. Segmentation subdivides an image into its constituent regions or objects.

Atlas of peripheral blood. The level to which the subdivision is carried out depends on the problem being solved.

Hallazgo de linfopenia incidental [Internet]. Table 5 shows the values achieved with the common equations related to the confusion matrix. The paper is organized as follows. After smoothing the image it was observed the presence of some artifacts that are not part of the objects of interest, which must be removed with the help of a median filter, and a couple of morphological filters. Computer-aided automatic analysis not only saves manpower and time, but also reduces the effects of human errors.


The first step was to separate the white blood cells from the red blood cells. On the other hand, neutrophils and eosinophils have a greater size than basophils, and have a clear differentiation in the amount of cytoplasm with respect to the monocytes and lymphocytes. Biblioteca Nacional de Medicina de Estados Unidos.

To segment the nuclei of the leukocytes we used the green channel Gsince in this channel the image presents more details and less additive noise. Hematology is the branch of medical science responsible for the study of the elements integrating the blood as well as their precursors, and the structural and biochemical disorders of these elements that can lead to a disease.

The algorithm k -NN k-Nearest Neighbororiginally proposed by Fix and Hodges [14], is a very simple “instance-based” learning algorithm. However, despite the simplicity and effectiveness, this method only applies to circular-shaped white blood cells such as lymphocytes.

Medical Library Utah; [citado 9 Feb ].

The task of segmenting them is carried out after the contrast enhancement of the adequately prepared smear and the prior transformation to a gray-level image of the commonly used color RGB image. Conganat; [citado 23 Peruferica ]. Hospital General Universitario Dr. Finally, we got the image without noise and artifacts as shown in Fig. Segmentation should stop when the objects of interest in an application have been isolated [1].