278 research outputs found
Assessment of left ventricle dynamic from cardiac magnetic resonance imaging by means a correspondence approach
In this research, an approach to assess the heart dynamics is reported. The
cardiac magnetic resonance images are considered for assessing the left ventricle motion and
deformation. The shape of the cavity is obtained by means a segmentation procedure based
on a clustering algorithm at an initial instant. This three-dimensional structure is used to
establish a region of interest around the border of the structure. An optical flow method allows
determining the displacement vector of this region and then defining the shapes of the cavity
during the all cardiac cycle. The points of the left ventricle are followed using the displacement
vectors in the cardiac cycle, obtaining thus, a dense motion field of the cavity. This approximate
deformation field is refined with a correspondence method that working in the three-dimensional
space. The mapping of the points that define the left ventricle in the cardiac cycle obtained
with the correspondence procedure are then used for computing a set of clinical parameters that
allows assessing the motion and deformation of this principal structure of the human heart. The
torsion, radial and longitudinal contraction are quantified. The obtained results are promising
for evaluating the heart dynamics
El sistema renal hídrico: una herramienta para la recuperación de humedales pampeanos
Actualmente los humedales son un centro de atención internacional debido a la importancia que se les reconoce como fuente de diversidad biológica y cultural, sustento de masas de agua de calidad, capacidad de purificación de aguas negras y grises, y mantenimiento de sistemas productivos; entre otras funciones. Es por eso que la protección de los mismos figura en la agenda de diversos organismos, gobiernos y referentes de relevancia internacional. El carácter de espontánea con que se ha producido la expansión Urbana e industrial en las últimas décadas, ejerce múltiples presiones sobre los recursos hídricos y en particular sobre los humedales afectando su calidad, cantidad y el acceso a ellos por parte de la población. Este es el caso de las laguna pampeanas, poco profundas, que no estratifican térmicamente, con tiempos de permanencia del agua y salinidad altamente variables, naturalmente meso-eutróficos, y actualmente bajo estrés ambiental manifiesto lo cual incrementa aún más sus contenidos de nutrientes, contaminantes como metales y pesticidas y sustenta la proliferación de florecimientos cianobacterianos. La eutrofización de cuerpos de agua constituye un problema ambiental persistente, caracterizado por una elevada carga de nutrientes, turbidez del agua, presencia de algas tóxicas, mortandad de pece por anoxias, enfermedades de origen hídrico y pérdida de diversidad biológica en los ecosistemas acuáticos (Carpenter et al. 1999). Esta situación ambiental afecta a las lagunas pampeanas, entre otros cuerpos de agua, y están relacionados con descargas puntuales no tratadas provenientes de áreas urbanas y con fuentes difusas de descargas que no están reguladas provenientes de diversas actividades industriales (Quiros, 2000). Una de las consecuencias de la eutrofización son los florecimientos algales nocivos (FAN), dominados fundamentalmente por distintas especies de cianobacterias, y favorecidos por el cambio climático (Codd y col., 1989; Paerl y Huisman, 2008). Otra de las consecuencias de los impactos antrópicos, es la presencia de metales pesados en estos cuerpos de agua. Sus efectos tóxicos sobre la biota y su dispersión en el ambiente dependen de su especiación, la cual esta a su vez relacionada con parámetros fisicoquímicos de los cuerpos de agua como pH y calidad y concentración de materia orgánica. En este contexto, la presencia de metales pesados en el agua puede generar bioacumulación, fenómeno que afecta a los organismos de todo el ecosistema y plantea consecuencias perjudiciales para la salud de todas las formas de vida
Uncertainty as key element in the analysis of X–ray angiography images
The X–ray angiography images are routinely used to assess the blood vessels. The
acquisition procedure considers a medical imaging system which allows obtaining views of the
vessel while the blood flows thought them. The X–ray source is influenced on the region to be
viewed and then, the projection of the all anatomical structures in the champ of view is shown
through an image intensifier. The information of the blood vessel is impacted for the other
structures. Additionally, the blood and the contrast product required in the acquisition are not
mixed homogeneously, producing artifacts in the images. Finally, the noise is also an impact
factor in the quality of the angiography images. In the coronary vessel case, the branches of the
network are superposed. In this paper, an enhancement procedure to diminish the uncertainty
associated to X–ray angiography images is reported. The relation between two versions of the
angiograms is determined using a fuzzy connector considering that this relation diminishes the
images intrinsic uncertainty. These versions correspond with images filtered with low-pass and
high-pass image filters, respectively. The technique is tested with images of the coronary and
kidney vessels. The qualitative results show a good enhanced of the angiography images
Developmental perspectives of numerical thinking for the interpretation of physical quantities
This research reveals the perspectives in the teaching of numerical thinking through a documentary review. The representation of physical elements such as functions, vectors and operators, and their subsequent interpretation through numerical thinking gives meaning to the physical quantities that such elements represent. A documentary sample integrated for 40 sources on numerical thinking such as articles published in indexed journals, postgraduate dissertations, and books is considered. A qualitative content analysis method is used. First, an encoding procedure is applied for tagging the extracted information from the source documents. Then, a split and merge procedure is considered in order to establish from the tags the dimensions and categories that allow determining the conceptual relationships that support the developmental perspectives of numerical thinking. The method reveals that the numerical thinking can be developed in the global context from four perspectives, namely, historical, theoretical, curricular, and social perspectives. From these results, an incorporation of the such perspectives can be institutionalized for promoting curricular, didactic and evaluative new proposals for numerical thinking teaching
New anisotropic diffusion operator in images filtering
The anisotropic di usion lters have become in the fundamental bases to address
the medical images noise problem. The main attributes of these lters are: the noise removal
e ectiveness and the preservation of the information belonging to the edges that delimit the
objects of an image. Due to these excellent attributes, through this article, a comparative study
is proposed between a new di usion operator and the Lorentz operator, proposed by the pioneers
of anisotropic di usion. For this, a strategy consisting of two phases is designed. In the rst,
called operator construction, the composition of functions is used to generate a new di usion
operator that meets with the conditions reported for this kind of the mathematical object. In the
second phase, denominated ltering, a synthetic cardiac images database, based on computed
tomography, is ltered using the aforementioned operators. According with the value obtained
for the peak of the signal-to-noise ratio, the new operator shows similar performance to the
Lorentz operator. The implementation of this new operator contributes to the generation of
new knowledge in digital image processing context
Pulmonary adenocarcinoma characterization using computed tomography images
Lung cancer is one of the pathologies that sensitively affects the health of human
beings. Particularly, the pathology called pulmonary adenocarcinoma represents 25% of all lung
cancers. In this research, we propose a semiautomatic technique for the characterization of a
tumor (adenocarcinoma type), present in a three-dimensional pulmonary computed tomography
dataset. Following the basic scheme of digital image processing, first, a bank of smoothing filters
and edge detectors is applied allowing the adequate preprocessing over the dataset images. Then,
clustering methods are used for obtaining the tumor morphology. The relative percentage error
and the accuracy rate were the metrics considered to determine the performance of the proposed
technique. The values obtained from the metrics used reflect an excellent correlation between
the morphology of the tumor, generated manually by a pneumologist and the values obtained by
the proposed technique. In the clinical and surgical contexts, the characterization of the detected
lung tumor is made in terms of volume occupied by the tumor and it allows the monitoring of
this disease as well as the activation of the respective protocols for its approach
Semi-automatic detection of the evolutionary forms of visceral leishmaniasis in microscopic blood smears
Leishmaniasis is a complex group of diseases caused by obligate unicellular and
intracellular eukaryotic protozoa of the leishmania genus. Leishmania species generate diverse
syndromes ranging from skin ulcers of spontaneous resolution to fatal visceral disease. These
syndromes belong to three categories: visceral leishmaniasis, cutaneous leishmaniasis and
mucosal leishmaniasis. The visceral leishmaniasis is based on the reticuloendothelial system
producing hepatomegaly, splenomegaly and lymphadenopathy. In the present article, a semiautomatic
segmentation strategy is proposed to obtain the segmentations of the evolutionary
shapes of visceral leishmaniasis called parasites, specifically of the type amastigote and
promastigote. For this purpose, the optical microscopy images containing said evolutionary
shapes, which are generated from a blood smear, are subjected to a process of transformation
of the color intensity space into a space of intensity in gray levels that facilitate their
subsequent preprocessing and adaptation. In the preprocessing stage, smoothing filters and
edge detectors are used to enhance the optical microscopy images. In a complementary way, a
segmentation technique that groups the pixels corresponding to each one of the parasites,
presents in the considered images, is applied. The results reveal a high correspondence between
the available manual segmentations and the semi-automatic segmentations which are useful for
the characterization of the parasites. The obtained segmentations let us to calculate areas and
perimeters associated with the parasites segmented. These results are very important in clinical
context where both the area and perimeter calculated are vital for monitoring the development
of visceral leishmaniasis
The rubric as an assessment strategy in the mathematical argumentation process
The article shares the proposal of an analytical rubric as a strategy for the assessment and monitoring of learning outcomes in students who develop an argumentative plot from the mathematics field, to solve any problem situation in daily life. The study was based on the theory of mathematical argumentation proposed by Duval and the contributions of León and Calderón, as well as the dimensions presented to us by the logical frameworks in the design of analytical rubrics. The research was developed under the social critical paradigm through the design of pedagogical action research, and the focus group technique was used for the collection of information composed by five professors from the department of basic sciences. As a result, a collective rubric that, in addition to generating processes of self-assessment and self-training in teachers, evidences a decrease in the existent subjectivity of the evaluation processes, thus strengthening its objectivity
Use of computational realistic models for the cardiac ejection fraction calculation
Ejection fraction is one of the most useful clinical descriptors to determine the cardiac
function of a subject. For this reason, obtaining the value of this descriptor is of vital importance
and requires high precision. However, in the clinical routine, to generate the mentioned
descriptor value, a geometric hypothesis is assumed, obtaining an approximate value for this
fraction, usually by excess, and which is a dependent-operator. The aim of the present work is
to propose the accurate calculation of the ejection fraction from realistic models, obtained
computationally, of the cardiac chamber called right ventricle. Normally, the geometric
hypothesis that makes this ventricle coincide with a pyramidal type geometric shape, is not
usually, fulfilled in subjects affected by several cardiac pathologies, so as an alternative to this
problem, the computational segmentation process is used to generate the morphology of the right
ventricle and from it proceeds to obtain, accurately, the ejection fraction value. In this sense, an
automatic strategy based on no-lineal filters, smart operator and region growing technique is
propose in order to generate the right ventricle ejection fraction. The results are promising due
we obtained an excellent correspondence between the manual segmentation and the automatic
one generated by the realistic models
Usefulness of cutting planes in the hierarchical segmentation of cardiac anatomical structures
A spatial geometric plane is defined by the three-dimensional coordinates of a pair of
spatial points and the direction that the normal vector establishes, which is formed by joining
those points by means of an oriented line segment. This type of planes, in three-dimensional
images, is extremely useful as an alternative solution to the problem of low contrast that exhibit
the anatomical structures present in cardiac computed tomography images. To do this, after using
a predetermined filter bank and in order to define a region of interest, a smart operator based on
least squares support vector machines is trained and validated in order to detect the
aforementioned coordinates which enables the location of the plane, in the three-dimensional
space that contains the considered images. Once the structure that is required to segment is
identified, a discriminant function is used that cancels all information not linked to this structure.
In this work, the segmentation of the left ventricle, based on region growing technique, is firstly
considered and then the left atrium is segmented considering region growing technique and an
inverse discriminant function. The results show an excellent correspondence relationship when
the spatial union of both structures is made
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