Image retargeting using stable paths

Media content adaptation is the action of transforming media files to adapt to device capabilities, usually related to mobile devices that require special handling because of their limited computational power, small screen size and constrained keyboard functionality. Image retargeting is one of such adaptations, transforming an image into another with different size. Tools allowing the author to imagery once and automatically retarget that imagery for a variety of different display devices are therefore of great interest. The performance of these algorithms is directly related with the preservation of the most important regions and features of the image. In this work, we introduce an algorithm for automatically retargeting images. We explore and extend a recently proposed algorithm on the literature. The central contribution is the introduction of the stable paths for image resizing, improving both the computational performance and the overall quality of the resulting image. The experimental results confirm the potential of the proposed algorithm

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

Automatic biometric identification based on fingerprintsis still one of the most reliable identification method in criminaland forensic applications. A critical step in fingerprintanalysis without human intervention is to automatically andreliably extract singular points from the input fingerprintimages. These singular points (cores and deltas) not onlyrepresent the characteristics of local ridge patterns but alsodetermine the topological structure (i.e., fingerprint type)and largely influence the orientation field. Poincaré Indexbasedmethods are one of the most common for singularpoints detection. However, these methods usually result inmany spurious detections. Therefore, we propose an enhancedversion 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 asmoothed orientation field and in the formulation of a newalgorithm to analyze the DORIC feature. Experimental resultsshow that the proposed algorithm is accurate and robust,giving better results than the best reported results sofar, with improvements in the range of 5% to 7%

Diffuse reflectance and machine learning techniques to differentiate colorectal cancer ex vivo

In this study, we used machine learning techniques to reconstruct the wavelength dependence of the absorption coefficient of human normal and pathological colorectal mucosa tissues. Using only diffuse reflectance spectra from the ex vivo mucosa tissues as input to algorithms, several approaches were tried before obtaining good matching between the generated absorption coefficients and the ones previously calculated for the mucosa tissues from invasive experimental spectral measurements. Considering the optimized match for the results generated with the multilayer perceptron regression method, we were able to identify differentiated accumulation of lipofuscin in the absorption coefficient spectra of both mucosa tissues as we have done before with the corresponding results calculated directly from invasive measurements. Considering the random forest regressor algorithm, the estimated absorption coefficient spectra almost matched the ones previously calculated. By subtracting the absorption of lipofuscin from these spectra, we obtained similar hemoglobin ratios at 410/550 nm: 18.9-fold/9.3-fold for the healthy mucosa and 46.6-fold/24.2-fold for the pathological mucosa, while from direct calculations, those ratios were 19.7-fold/10.1-fold for the healthy mucosa and 33.1-fold/17.3-fold for the pathological mucosa. The higher values obtained in this study indicate a higher blood content in the pathological samples used to measure the diffuse reflectance spectra. In light of such accuracy and sensibility to the presence of hidden absorbers, with a different accumulation between healthy and pathological tissues, good perspectives become available to develop minimally invasive spectroscopy methods for in vivo early detection and monitoring of colorectal cancer.The application of machine learning methods to noninvasivelike diffuse reflectance spectra allowed us to reconstruct the absorption coefficient spectra of human healthy and pathological mucosa tissues from the colorectal wall. Consequently, we were able to obtain differentiated blood and pigment content in both tissues, which can be used for the development of new noninvasive diagnostic methods for colorectal cancer.The work of L. M. Oliveira was supported by the Portuguese Science Foundation (Grant No. FCT-UIDB/04730/2020). The work of V. V. Tuchin was supported by a grant of the Government of the Russian Federation (Registration No. 2020-220-08-2389).info:eu-repo/semantics/publishedVersio

Weakly-supervised classification of HER2 expression in breast cancer haematoxylin and eosin stained slides

Human epidermal growth factor receptor 2 (HER2) evaluation commonly requires immunohistochemistry (IHC) tests on breast cancer tissue, in addition to the standard haematoxylin and eosin (H&E) staining tests. Additional costs and time spent on further testing might be avoided if HER2 overexpression could be effectively inferred from H&E stained slides, as a preliminary indication of the IHC result. In this paper, we propose the first method that aims to achieve this goal. The proposed method is based on multiple instance learning (MIL), using a convolutional neural network (CNN) that separately processes H&E stained slide tiles and outputs an IHC label. This CNN is pretrained on IHC stained slide tiles but does not use these data during inference/testing. H&E tiles are extracted from invasive tumour areas segmented with the HASHI algorithm. The individual tile labels are then combined to obtain a single label for the whole slide. The network was trained on slides from the HER2 Scoring Contest dataset (HER2SC) and tested on two disjoint subsets of slides from the HER2SC database and the TCGA-TCIA-BRCA (BRCA) collection. The proposed method attained 83.3% classification accuracy on the HER2SC test set and 53.8% on the BRCA test set. Although further efforts should be devoted to achieving improved performance, the obtained results are promising, suggesting that it is possible to perform HER2 overexpression classification on H&E stained tissue slides.publishersversionpublishe

Paper-Based Biosensors for Analysis of Water

The presence of contaminants in water generates a great concern worldwide. As contaminants, we can refer different classes of chemicals, such as pharmaceuticals, personal care products, heavy metals, and also microorganisms, such as waterborne pathogens. Some of the chemical compounds have the potential to bioaccumulate in the aquatic biota. Hence, the development of simple and portable methods for the detection of contaminants in the aquatic environment can improve their monitoring and, consequently, the study of their environmental impact. In this context, the development of paper-based analytical tools and also of biosensor devices has been exploited for quantitative and semiquantitative analysis of several contaminants in different water matrices. The association of these two analytical strategies can provide the implementation of low-cost, portable, and easily handled methods for detecting chemical and biological contaminations in water. In this chapter, we provide a review of the developed paper-based analytical biosensors, highlighting the features of the paper-based (paper substrate and fabrication procedures) and biosensor devices (transducers and biorecognition elements). Moreover, the application of the referred paper-based biosensors for the detection of different water contaminants (pathogens, pharmaceuticals, and heavy metals) in environmental and wastewater samples is discussed

Avaliação da aptidão e actividade física associadas à saúde em adolescentes do 3º ciclo do ensino básico de diferentes níveis socioeconómicos

Projeto de investigaçãoA Actividade Física tem efeitos benéficos sobre a saúde, sendo a idade escolar o período mais adequado para a aquisição de hábitos saudáveis e promoção da saúde. Pretende-se conhecer e avaliar os níveis de aptidão e actividade física dos alunos do 9º ano de diferentes níveis socioeconómicos de escolas da zona norte de Portugal. Para avaliação será utilizada a bateria de testes do Fitnessgram e acelerómetros. Será aplicado ainda um questionário para caracterizar a sua situação socioeconómica.Fundação para a Ciência e a Tecnologia (FCT) - unidade de investigação 31

Valorizing coffee silverskin based on its phytochemicals and antidiabetic potential: from lab to a pilot scale

This study investigates the possibility of valorizing coffee silverskin through the recovery of its bioactive compounds using a sustainable extraction method that could be industrially applied. For that, aqueous extracts were prepared using ultrasonic-assisted extraction (laboratorial scale) and, for comparison, a scale-up of the process was developed using the Multi-frequency Multimode Modulated technology. A concentration procedure at the pilot scale was also tested. The three types of extracts obtained were characterized regarding caffeine and chlorogenic acids contents, and the effects on intestinal glucose and fructose uptake (including sugar transporters expression) in human intestinal epithelial (Caco-2) cells were ascertained. The phytochemical contents of the extracts prepared at the laboratory and pilot scale were comparable (caffeine: 27.7 vs. 29.6 mg/g freeze-dried extract; 3-, 4-, and 5-caffeoylquinic acids: 0.19 vs. 0.31, 0.15 vs. 0.42, and 1.04 vs. 1.98 mg/g, respectively; 4- and 5- feruloylquinic acids: 0.39 vs. 0.43 and 1.05 vs. 1.32 mg/g, respectively). Slight differences were noticed according to the extracts preparation steps, but in general, all the extracts promoted significant inhibitions of [1,2-3H(N)]-deoxy-D-glucose and 14C-D-fructose uptake, which resulted mainly from a decrease on the facilitative glucose transporter 2 (GLUT2) and sodium-glucose linked transporter 1 (SGLT1) genes expression but not on the expression of the facilitative glucose transporter 5 (GLUT5) gene. Moreover, a synergistic effect of caffeine and 5-caffeoylquinic acid on sugars uptake was found. The results clearly show that the Multi-frequency Multimode Modulated technology is a viable option to be applied at an industrial level to recover bioactive components from silverskin and obtain extracts with antidiabetic potential that could be used to develop functional food products or dietary supplements.The open access publication fee of this paper was funded by the AgriFood XXI I&D&I project (NORTE-01-0145-FEDER-000041) cofinanced by European Regional Development Fund (ERDF) through the NORTE 2020 (Programa Operacional Regional do Norte 2014/2020)

Arthroscopic repair of ankle instability with all-soft knotless anchors

In recent years, arthroscopic and arthroscopically assisted techniques have been increasingly used to reconstruct the lateral ligaments of the ankle. Besides permitting the treatment of several comorbidities, arthroscopic techniques are envisioned to lower the amount of surgical aggression and to improve the assessment of anatomic structures. We describe our surgical technique for arthroscopic, two-portal ankle ligament repair using an all-soft knotless anchor, which is made exclusively of suture material. This technique avoids the need for classic knot-tying methods. Thus it diminishes the chance of knot migration caused by pendulum movements. Moreover, it avoids some complications that have been related to the use of metallic anchors and some currently available biomaterials. It also prevents prominent knots, which have been described as a possible cause of secondary complaints.info:eu-repo/semantics/publishedVersio

3D digital breast cancer models with multimodal fusion algorithms

Breast cancer image fusion consists of registering and visualizing different sets of a patient synchronized torso and radiological images into a 3D model. Breast spatial interpretation and visualization by the treating physician can be augmented with a patient-specific digital breast model that integrates radiological images. But the absence of a ground truth for a good correlation between surface and radiological information has impaired the development of potential clinical applications. A new image acquisition protocol was designed to acquire breast Magnetic Resonance Imaging (MRI) and 3D surface scan data with surface markers on the patient's breasts and torso. A patient-specific digital breast model integrating the real breast torso and the tumor location was created and validated with a MRI/3D surface scan fusion algorithm in 16 breast cancer patients. This protocol was used to quantify breast shape differences between different modalities, and to measure the target registration error of several variants of the MRI/3D scan fusion algorithm. The fusion of single breasts without the biomechanical model of pose transformation had acceptable registration errors and accurate tumor locations. The performance of the fusion algorithm was not affected by breast volume. Further research and virtual clinical interfaces could lead to fast integration of this fusion technology into clinical practice.publishersversionpublishe