2019
Authors
Faria, MT; Rodrigues, S; Dias, D; Rego, R; Rocha, H; Sa, F; Oliveira, A; Campelo, M; Pereira, J; Rocha Goncalves, F; Cunha, JPS; Martins, E;
Publication
EUROPEAN HEART JOURNAL
Abstract
2019
Authors
Faria, MT; Rodrigues, S; Dias, D; Rego, R; Rocha, H; Sa, F; Oliveira, A; Campelo, M; Pereira, J; Rocha Goncalves, F; Cunha, JPS; Martins, E;
Publication
EUROPEAN HEART JOURNAL
Abstract
2019
Authors
Clemente, M; Mendes, J; Moreira, A; Bernardes, G; Van Twillert, H; Ferreira, A; Amarante, JM;
Publication
Journal of Oral Biology and Craniofacial Research
Abstract
Background/objective: Playing a wind instrument implies rhythmic jaw movements where the embouchure applies forces with different directions and intensities towards the orofacial structures. These features are relevant when comparing the differences between a clarinettist and a saxophone player embouchure, independently to the fact that both belong to the single-reed instrument group, making therefore necessary to update the actual classification. Methods: Lateral cephalograms were taken to single-reed, double-reed and brass instrumentalists with the purpose of analyzing the relationship of the mouthpiece and the orofacial structures. Results: The comparison of the different wind instruments showed substantial differences. Therefore the authors purpose a new classification of wind instruments: Class 1 single-reed mouthpiece, division 1– clarinet, division 2 –saxophone; Class 2 double-reed instruments, division 1– oboe, division 2– bassoon; Class 3 cup-shaped mouthpiece, division 1– trumpet and French horn, division 2- trombone and tuba; Class 4 aperture mouthpieces, division 1– flute, division 2 – transversal flute and piccolo. Conclusions: Elements such as dental arches, teeth and lips, assume vital importance at a new nomenclature and classification of woodwind instruments that were in the past mainly classified by the type of mouthpiece and not taking into consideration its relationship with their neighboring structures. © 2019 Craniofacial Research Foundation
2019
Authors
Seixas, A; Vilas Boas, MD; Carvalho, R; Coelho, T; Ammer, K; Vilas Boas, JP; Mendes, J; Cunha, JPS; Vardasca, R;
Publication
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION
Abstract
Skin temperature regulation is dependent on the autonomic nervous system function, which may be impaired in patients with neuropathy. Literature reporting thermographic assessment of patients with established diagnosis of Diabetic Foot (DF) is scarce, but this information is completely absent in patients suffering from Transthyretin Familial Amyloid Polyneuropathy (TTR-FAP). The aim of this study is to compare skin temperature distribution in patients with DF and TTR-FAP. Thermograms of the dorsal and plantar surfaces of twelve neuropathic patients, six with DF and six with TTR-FAP, were assessed and compared. Skin temperature was significantly higher in the diabetic foot group, in both regions of interest. Thermal symmetry values were high, but similar in both groups. The bias between the right and left foot was smaller, with smaller limits of agreement in TTR-FAP patients, suggesting a lower agreement between the temperature of the right and left feet in DF patients.
2019
Authors
Shakibapour, E; Cunha, A; Aresta, G; Mendonca, AM; Campilho, A;
Publication
EXPERT SYSTEMS WITH APPLICATIONS
Abstract
This paper proposes a new methodology to automatically segment and measure the volume of pulmonary nodules in lung computed tomography (CT) scans. Estimating the malignancy likelihood of a pulmonary nodule based on lesion characteristics motivated the development of an unsupervised pulmonary nodule segmentation and volume measurement as a preliminary stage for pulmonary nodule characterization. The idea is to optimally cluster a set of feature vectors composed by intensity and shape-related features in a given feature data space extracted from a pre-detected nodule. For that purpose, a metaheuristic search based on evolutionary computation is used for clustering the corresponding feature vectors. The proposed method is simple, unsupervised and is able to segment different types of nodules in terms of location and texture without the need for any manual annotation. We validate the proposed segmentation and volume measurement on the Lung Image Database Consortium and Image Database Resource Initiative - LIDC-IDRI dataset. The first dataset is a group of 705 solid and sub-solid (assessed as part-solid and non-solid) nodules located in different regions of the lungs, and the second, more challenging, is a group of 59 sub-solid nodules. The average Dice scores of 82.35% and 71.05% for the two datasets show the good performance of the segmentation proposal. Comparisons with previous state-of-the-art techniques also show acceptable and comparable segmentation results. The volumes of the segmented nodules are measured via ellipsoid approximation. The correlation and statistical significance between the measured volumes of the segmented nodules and the ground-truth are obtained by Pearson correlation coefficient value, obtaining an R-value >= 92.16% with a significance level of 5%.
2019
Authors
Paiva, JS; Ribeiro, RSR; Jorge, PAS; Rosa, CC; Sampaio, P; Cunha, JPS;
Publication
OPTICAL FIBERS AND SENSORS FOR MEDICAL DIAGNOSTICS AND TREATMENT APPLICATIONS XIX
Abstract
In view of the growing importance of nanotechnologies, the detection of nanoparticles type in several contexts has been considered a relevant topic. Several organisms, including the National Institutes of Health, have been highlighting the urge of developing nanoparticles exposure risk assessment assays, since very little is known about their physiological responses. Although the identi fi cation/characterization of synthetically produced nanoparticles is considered a priority, there are many examples of \ naturally" generated nanostructures that provide useful information about food components or human physiology. In fact, several nanoscale extracellular vesicles are present in physiological fluids with high potential as cancer biomarkers. However, scientists have struggled to fi nd a simple and rapid method to accurately detect/identify nanoparticles, since their majority have diameters between 100-150 nm -far below the di ff raction limit. Currently, there is a lack of instruments for nanoparticles detection and the few instrumentation that is commonly used is costly, bulky, complex and time consuming. Thus, considering our recent studies on particles identi fi cation through back-scattering, we examined if the time/frequency-domain features of the back-scattered signal provided from a 100 nm polystyrene nanoparticles suspension are able to detect their presence only by dipping a polymeric lensed optical fi ber in the solution. This novel technique allowed the detection of synthetic nanoparticles in distilled water versus \ blank solutions" (only distilled water) through Multivariate Statistics and Arti fi cial Intelligence (AI)-based techniques. While the state-of-the-art methods do not o ff er a ff ordable and simple approaches for nanoparticles detection, our technique can contribute for the development of a device with innovative characteristics.
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