Morphological analysis of cells by means of an elastic metric in the shape space

Shape analysis is of great importance in many fields, such as computer vision, medical imaging, and computational biology. This analysis can be performed considering shapes as closed planar curves in the shape space. This approach has been used for the first time to obtain the morphological classification of erythrocytes in digital images of sickle cell disease considering the shape space S1, which has the property of being isometric to an infinite-dimensional Grassmann manifold of two-dimensional subspaces (Younes et al., 2008), without taking advantage of all the features offered by the elastic metric related to the possibility of stretching and bending of the curves. In this paper, we study this deformation in the shape space, S2, which is based on the representation of closed planar curves by means of the square-root velocity function (SRVF) (Srivastava et al., 2011), using the elastic metric of this space to obtain more efficient geodesics and geodesic lengths between planar curves. Supervised classification with this approach achieved an accuracy of 94.3%, classification using templates achieved 94.2% and unsupervised clustering in three groups achieved 94.7%, considering three classes of erythrocytes: normal, sickle, and with other deformations. These results are better than those previously achieved in the morphological analysis of erythrocytes and the method can be used in different applications related to the treatment of sickle cell disease, even in cases where it is necessary to study the process of evolution of the deformation, something that can not be done in a natural way in the feature space

Clasificación de eritrocitos empleando modelos ocultos de Márkov

Se realiza un estudio del desempeño de los modelos ocultos de Márkov (HMM) en la clasificación morfológica supervisada de eritrocitos en muestras de sangre periférica de pacientes con anemia drepanocítica. Los contornos se representan de forma novedosa considerando las diferencias angulares en la curvatura de los puntos del mismo. El entrenamiento de cada modelo se realiza tanto con la descripción normal de los contornos como con la representación de la rotación de los mismos, para garantizar una mayor estabilidad en los parámetros estimados. Se desarrolla un proceso de validación cruzada de 5x1 para estimación del error. Se obtienen las medidas de sensibilidad, precisión y especificidad de la clasificación. Los mejores resultados en cuanto a sensibilidad se obtienen al clasificar eritrocitos pertenecientes a dos clases: normales (96%) y elongados (99%). Al considerar además una clase de eritrocitos con otras deformaciones los mejores resultados se obtienen realizando el entrenamiento de los modelos con la rotación de todos los contornos, que alcanzó sensibilidades de normales (94%), elongados (82%) y con otras deformaciones (76%). Palabras Clave: clasificación morfológica de eritrocitos, modelos ocultos de Márkov, representación de contornos

Métodos computacionales para estudio de la anemia drepanocítica

El procesamiento de imágenes digitales y la visión por computador son ampliamente utilizados en medicina actualmente y son de gran interés las propuestas de nuevos métodos de análisis automatizado de imágenes digitales o mejorar la eficiencia de los existentes. En este trabajo se desarrollaron métodos nuevos para estudiar computacionalmente a través de imágenes de muestras de sangre la drepanocitosis, dolencia con alta incidencia mundial y en Cuba, sobre todo en la región oriental. Se propusieron nuevos métodos de análisis de formas, obtenidos a partir de resultados clásicos de geometría integral y nuevas propuestas de visión por computador para evaluar trastornos neurofisiológicos asociados a través del estudio de las expresiones faciales del paciente. La validación estadística realizada comprobó la superioridad de estos métodos sobre otros, se determinó que son válidos para ser introducidos en software de apoyo para mejorar la calidad de la atención médica.Palabras clave: análisis de forma, análisis de expresiones faciales, drepanocitosis.</p

Diagnosis support of sickle cell anemia by classifying red blood cell shape in peripheral blood images

[eng] Red blood cell (RBC) deformation is the consequence of several diseases, including sickle cell anemia, which causes recurring episodes of pain and severe pronounced anemia. Monitoring patients with these diseases involves the observation of peripheral blood samples under a microscope, a time-consuming procedure. Moreover, a specialist is required to perform this technique, and owing to the subjective nature of the observation of isolated RBCs, the error rate is high. In this paper, we propose an automated method for differentially enumerating RBCs that uses peripheral blood smear image analysis. In this method, the objects of interest in the image are segmented using a Chan-Vese active contour model. An analysis is then performed to classify the RBCs, also called erythrocytes, as normal or elongated or having other deformations, using the basic shape analysis descriptors: circular shape factor (CSF) and elliptical shape factor (ESF). To analyze cells that become partially occluded in a cluster during sample preparation, an elliptical adjustment is performed to allow the analysis of erythrocytes with discoidal and elongated shapes. The images of patient blood samples used in the study were acquired by a clinical laboratory specialist in the Special Hematology Department of the 'Dr. Juan Bruno Zayas' General Hospital in Santiago de Cuba. A comparison of the results obtained by the proposed method in our experiments with those obtained by some state-of-the-art methods showed that the proposed method is superior for the diagnosis of sickle cell anemia. This superiority is achieved for evidenced by the obtained F-measure value (0.97 for normal cells and 0.95 for elongated ones) and several overall multiclass performance measures. The results achieved by the proposed method are suitable for the purpose of clinical treatment and diagnostic support of sickle cell anemia