Hélder P. Oliveira

Experimental and Theoretical Data on the Mechanism by Which Red Wine Anthocyanins Are Transported through a Human MKN-28 Gastric Cell Model

The gastric absorption of red wine anthocyanins was evaluated using a gastric MKN-28 cell barrier model. Anthocyanin transport was not affected by the presence of 4% ethanol and decreased with the increase of pH. Gastric cells pretreated with anthocyanins were found to increase anthocyanin transport. The presence of d-(+)-glucose was found to decrease anthocyanin uptake, suggesting the involvement of glucose transporters. RT-PCR assays revealed that GLUT1, GLUT3, and MCT1 transporters were expressed in MKN-28 cells. Computational studies were performed to provide a structural characterization of the binding site of hGLUT1 to glucose or different anthocyanins under different forms. Docking results demonstrated that anthocyanins can bind to glucose transporters from both intracellular and extracellular sides. Anthocyanins seem to enter into the transporter by two main conformations: B ring or glucose. From MD simulations, hGLUT1 was found to form complexes with all anthocyanins tested in the different protonation states.

An accurate and interpretable model for BCCT.core

Breast Cancer Conservative Treatment (BCCT) is considered nowadays to be the most widespread form of locor-regional breast cancer treatment. However, aesthetic results are heterogeneous and difficult to evaluate in a standardized way. The limited reproducibility of subjective aesthetic evaluation in BCCT motivated the research towards objective methods. A recent computer system (BCCT.core) was developed to objectively and automatically evaluate the aesthetic result of BCCT. The system is centered on a support vector machine (SVM) classifier with a radial basis function (RBF) used to predict the overall cosmetic result from features computed on a digital photograph of the patient. However, this classifier is not ideal for the interpretation of the factors being used in the prediction. Therefore, an often suggested improvement is the interpretability of the model being used to assess the overall aesthetic result. In the current work we investigate the accuracy of different interpretable methods against the model currently deployed in the BCCT.core software. We compare the performance of decision trees and linear classifiers with the RBF SVM currently in BCCT.core. In the experimental study, these interpretable models shown a similar accuracy to the currently used RBF SVM, suggesting that the later can be replaced without sacrificing the performance of the BCCT.core.

Methods for the Aesthetic Evaluation of Breast Cancer Conservation Treatment: A Technological Review

Breast-conserving approaches aim to attain better aesthetic results in addition to local control and achieving survival rates equivalent to mastectomy in patients with breast cancer. While the oncologic outcome of breast conserva- tion procedures is easily estimated objectively by disease-free and overall survival rates, the cosmetic outcome has no standard of evaluation. Although breast conservation techniques have been widely studied, different forms of evaluation and heterogeneous working practices have contributed to different aesthetic results. As this scenario suggests, the evalua- tion of aesthetic results should be mandatory in any institution performing breast cancer treatment, contributing to the im- provement of current strategies by enabling the identification of variables which have a significant impact on the final aes- thetic result. In the process of assessing cosmetic outcomes there are several important issues that should be considered: which factors have a crucial impact on the cosmetic outcome of Breast Cancer Conservation Treatment (BCCT); which parameters or features should be evaluated in the cosmetic assessment of BCCT; how patients are evaluated; which scales are used in this evaluation; which methods and technological solutions are available for the evaluation of cosmetic results of BCCT. In this paper we try to discuss all these questions, with an emphasis on the objective methods and corresponding tech- nologies used in the aesthetic evaluation of BCCT. The most relevant publications related to the mentioned topics are pre- sented, critically analysed and put in chronological perspective. Current and future trends are also discussed.

Closed Shortest Path in the Original Coordinates with an Application to Breast Cancer

Breast cancer is one of the most mediated malignant diseases, because of its high incidence and prevalence, but principally due to its physical and psychological invasiveness. The study of this disease using computer science tools resorts often to the image segmentation operation. Image segmentation, although having been extensively studied, is still an open problem. Shortest path algorithms are extensively used to tackle this problem. There are, however, applications where the starting and ending positions of the shortest path need to be constrained, defining a closed contour enclosing a previously detected seed. Mass and calcification segmentation in mammograms and areola segmentation in digital images are two particular examples of interest within the field of breast cancer research. Usually the closed contour computation is addressed by transforming the image into polar coordinates, where the closed contour is transformed into an open contour between two opposite margins. In this work, after illustrating some of the limitations of this approach, we show how to compute the closed contour in the original coordinate space. After defining a directed acyclic graph appropriate for this task, we address the main difficulty in operating in the original coordinate space. Since small paths collapsing in the seed point are naturally favored, we modulate the cost of the edges to counterbalance this bias. A thorough evaluation is conducted with datasets from the breast cancer field. The algorithm is shown to be fast and reliable and suffers no loss in resolution.

A Nonlinear Model Predictive Control of an Omni-Directional Mobile Robot

This paper presents a nonlinear model based predictive controller (NMPC) for trajectory tracking of a mobile robot. Methods of numerical optimization to perform real time nonlinear minimization of the cost function are used. The cost function penalizes the robot position error, the robot orientation angle error and the control effort. Experimental results of the trajectories following and the performance of the methods of optimization are presented.

MobILive 2014 - Mobile Iris Liveness Detection Competition

Biometric systems based on iris are vulnerable to several attacks, particularly direct attacks consisting on the presentation of a fake iris to the sensor. The development of iris liveness detection techniques is crucial for the deployment of iris biometric applications in daily life specially in the mobile biometric field. The 1st Mobile Iris Liveness Detection Competition (MobILive) was organized in the context of IJCB2014 in order to record recent advances in iris liveness detection. The goal for (MobILive) was to contribute to the state of the art of this particular subject. This competition covered the most common and simple spoofing attack in which printed images from an authorized user are presented to the sensor by a non-authorized user in order to obtain access. The benchmark dataset was the MobBIOfake database which is composed by a set of 800 iris images and its corresponding fake copies (obtained from printed images of the original ones captured with the same handheld device and in similar conditions). In this paper we present a brief description of the methods and the results achieved by the six participants in the competition.

A 3D low-cost solution for the aesthetic evaluation of breast cancer conservative treatment

Breast cancer conservative treatment (BCCT) is now the preferred technique for breast cancer treatment. The limited reproducibility of standard aesthetic evaluation methods led to the development of objective methods, such as the software tool Breast Cancer Conservative Treatment.cosmetic results (BCCT.core). Although results are satisfying, there are still limitations concerning complete automation and the inability to measure volumetric information. With the fundamental premise of maintaining the system a low-cost tool, this work studies the incorporation of the Microsoft Kinect sensor in BCCT evaluations. The aim is to enable the automatic joint detection of prominent points, both on depth and RGB images. Afterwards, using those prominent points, it is possible to obtain two-dimensional and volumetric features. Finally, the aesthetic result is achieved using machine learning techniques converted automatically from the set of measures defined. Experimental results show that the proposed algorithm is acc...

Simultaneous detection of prominent points on breast cancer conservative treatment images

Breast Cancer Conservative Treatment (BCCT) is now the preferred technique for breast cancer treatment. The limited reproducibility of standard aesthetic evaluation methods led to the development of objective methods, such as Breast Cancer Conservative Treatment.cosmetic results (BCCT.core) software tool. Although the satisfying results, there are still limitations concerning complete automation and the inability to measure volumetric information. With the fundamental premise of maintaining the system as a low-cost tool, the incorporation of the Microsoft Kinect sensor in BCCT evaluations was studied. The aim with this work is to enable the simultaneous detection of breast contour and breast peak points using depth-map data. Experimental results show that the proposed algorithm is accurate and robust for a wide number of patients. Additionally, comparatively to previous research, the procedure for detecting prominent points was automated.

A new method for the detection of singular points in fingerprint images

Automatic biometric identification based on fingerprints is still one of the most reliable identification method in criminal and forensic applications. A critical step in fingerprint analysis without human intervention is to automatically and reliably extract singular points from the input fingerprint images. These singular points (cores and deltas) not only represent the characteristics of local ridge patterns but also determine the topological structure (i.e., fingerprint type) and largely influence the orientation field. Poincare¿ Index-based methods are one of the most common for singular points detection. However, these methods usually result in many spurious detections. Therefore, we propose an enhanced version of the method presented by Zhou et al. [13] that introduced a feature called DORIC to improve the detection. Our principal contribution lies in the adoption of a smoothed orientation field and in the formulation of a new algorithm to analyze the DORIC feature. Experimental results show that the proposed algorithm is accurate and robust, giving better results than the best reported results so far, with improvements in the range of 5% to 7%.

Development of a BCCT Quantitative 3D Evaluation System through Low-Cost Solutions

Breast cancer is one of the most mediated malignant diseases, because of its high incidence and prevalence, but principally because of its physical and psychological invasivity. Breast Cancer Conservative Treatments (BCCT) allows a local control of the disease, with a survival similar to that obtained with a mastectomy, but with a better aesthetic result: the tumor is excised together with a small healthy tissue layer. In BCCT the surgical outcome depends on several factors, many of them difficult to assess, thus leading to a significantly heterogeneous results. For this reason, it is fundamental to evaluate specific surgical procedures on the basis of their aesthetic outcome through specific quantitative tools. The Breast Cancer Conservative Treatment.cosmetic results (BCCT.core), is a software recently developed with the objective to overcome the limitations of reproducibility and objectivity of the methods currently used to evaluate the aesthetic result of BCCT. This software is based on the comparison between the treated and non-treated breast in frontal photographs from the patients. Several indices related to the surgical aesthetic result are automatically obtained from the image, making the evaluation fast, easy and reproducible. Although the BCCT.core system presents satisfactory results, presents a significant limitation. The female breast is a complex three dimensional (3D) object and its boundaries are rather fuzzily defined in two dimensional (2D) pictures, thus making difficult the body landmarks identification. On the contrary, the use of a 3D model would allow the comparison between real geometrical characteristics of the breasts including the possibility of estimating volume and 3D surface differences, in order to plan future surgical interventions. The goal of this work is the development of a simple 3D model of a female torso, using low-cost solutions, namely: a reconstruction algorithm from two uncalibrated views, through epipolar geometry approach and making use of a Kinect sensor device. The created model will be used in an updated version of a BCCT.core to obtain a full 3D aesthetic assessment of the surgical outcome. With the inclusion of measurements extracted from the 3D model, aiming to improve the global assessment result, without increasing its complexity, as the pictures are acquired with a single camera without requiring any calibration procedure.