Browsing by Author "Chan, Debora"
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artículo de publicación periódica.listelement.badge Low-cost robust estimation for the single-look 𝒢I0 model using the Pareto distribution(2020) Chan, Debora; Rey, Andrea; Gambini, Juliana; Frery, Alejandro C."The statistical properties of Synthetic Aperture Radar (SAR) image texture reveal useful target characteristics. It is well-known that these images are affected by speckle and prone to extreme values due to double bounce and corner reflectors. The G0 I distribution is flexible enough to model different degrees of texture in speckled data. It is indexed by three parameters: α, related to the texture, γ , a scale parameter, and L, the number of looks. Quality estimation of α is essential due to its immediate interpretability. In this letter, we exploit the connection between the G0 I and Pareto distributions. With this, we obtain six estimators that have not been previously used in the SAR literature. We compare their behavior with others in the noisiest case for monopolarized intensity data, namely single look case. We evaluate them using Monte Carlo methods for noncontaminated and contaminated data, considering convergence rate, bias, mean squared error, and computational time. We conclude that two of these estimators based on the Pareto law are the safest choices when dealing with actual data and small samples, as is the case of despeckling techniques and segmentation, to name just two applications. We verify the results with an actual SAR image."ponencia en congreso.listelement.badge Methods and frameworks for sampling 𝒢I0 data(2017) Chan, Debora; Rey, Andrea; Gambini, Juliana; Cassetti, Julia; Frery, Alejandro C."The 𝒢I0 distribution is a competitive tool for SAR image description. This distribution is useful for describing speckled imagery because it models adequately areas with different degrees of texture. Data simulation is crucial for the development of new methods of automatic interpretation of this type of images. We compare four alternatives for generating data under the 𝒢I0 distribution. The experiments are performed on a variety of programming languages and, a number of criteria to test the fidelity of the generated data are applied."artículo de publicación periódica.listelement.badge Object detection and statistical analysis of microscopy image sequences(2022) Hurovitz, Sasha Ivan; Chan, Debora; Ramele, Rodrigo; Gambini, Juliana"Confocal microscope images are wide useful in medical diagnosis and research. The automatic interpretation of this type of images is very important but it is a challenging endeavor in image processing area, since these images are heavily contaminated with noise, have low contrast and low resolution. This work deals with the problem of analyzing the penetration velocity of a chemotherapy drug in an ocular tumor called retinoblastoma. The primary retinoblastoma cells cultures are exposed to topotecan drug and the penetration evolution is documented by producing sequences of microscopy images. It is possible to quantify the penetration rate of topotecan drug because it produces fluorescence emission by laser excitation which is captured by the camera. In order to estimate the topotecan penetration time in the whole retinoblastoma cell culture, a procedure based on an active contour detection algorithm, a neural network classifier and a statistical model and its validation, is proposed. This new inference model allows to estimate the penetration time. Results show that the penetration mean time strongly depends on tumorsphere size and on chemotherapeutic treatment that the patient has previously received."artículo de publicación periódica.listelement.badge Sampling from the 𝒢I0 distribution(2018-12) Chan, Debora; Rey, Andrea; Gambini, Juliana; Frery, Alejandro C."Synthetic Aperture Radar (SAR) images are widely used in several environmental applications because they provide information which cannot be obtained with other sensors. The 𝒢I0 distribution is an important model for these images because of its flexibility (it provides a suitable way for modeling areas with different degrees of texture, reflectivity and signal-to-noise ratio) and tractability (it is closely related to the Snedekor-F, Pareto Type II, and Gamma distributions). Simulated data are important for devising tools for SAR image processing, analysis and interpretation, among other applications. We compare four ways for sampling data that follow the 𝒢I0 distribution, using several criteria for assessing the quality of the generated data and the consumed processing time. The experiments are performed running codes in four different programming languages. The experimental results indicate that although there is no overall best method in all the considered programming languages, it is possible to make specific recommendations for each one."ponencia en congreso.listelement.badge Speckle noise reduction in SAR images using information theory(2020) Chan, Debora; Gambini, Juliana; Frery, Alejandro C."In this work, a new nonlocal means filter for single-look speckled data using the Shannon and Renyi entropies is proposed. The measure of similarity between a central window and patches of the image is based on a statistical test for comparing if two samples have the same entropy and hence have the same distribution. The results are encouraging, as the filtered image has better signal-to-noise ratio, it preserves the mean, and the edges are not severely blurred."ponencia en congreso.listelement.badge Time estimation of topotecan penetration in retinoblastoma cells through image sequence analysis(2020) Chan, Debora; Winter, Úrsula; Schaiquevich, Paula; Ramele, Rodrigo; Gambini, Juliana"Retinoblastoma is the most common intraocular tumor in childhood. Topotecan has been widely used as an antineoplastic agent for retinoblastoma treatment. Topotecan penetration into living tumorspheres is quantified using confocal microscopy. This fluorescent drug dyes the living tissue and it can be recorded in a sequence of images over a period of time. The effective penetration of the drug depends on culture characteristics and requires a very specific timing. This penetration time is calculated empirically by an expert. The purpose of this work is to offer a statistical model to automatically estimate the penetration time of topotecan in the cell, based on the information obtained from a sequence of tumorsphere images."ponencia en congreso.listelement.badge Topotecan penetration assessment in retinoblastoma cells using Shannon entropy and coefficient of variation(2019-09) Howlin, Marcelo; Chan, Debora; Ramele, Rodrigo; Gambini, Juliana"Retinoblastoma is a common intraocular tumor of childhood. One of the medications used as an antineoplastic agent for retinoblastoma treatment is topotecan. Its penetration into living tumorspheres is quantified using confocal microscopy. Topotecan is a fluorescent drug and it dyes the living tissue. Then, it is recorded in a sequence of images over a period of time. The effective penetration of the drug depends on culture characteristics and requires a very specific timing which is calculated empirically by an expert. The purpose of this work is to offer a model to automatically estimate and evaluate the penetration time of topotecan in a cell, based on the information obtained from a sequence of tumorsphere images and using Shannon entropy and coefficient of variation."