Resumo em Inglês:

Abstract Introduction Numerical phantoms are important tools to design, calibrate and evaluate several methods in various image-processing applications, such as echocardiography and mammography. We present a framework for creating ultrasound numerical deformable phantoms based on Finite Element Method (FEM), Linear Isomorphism and Field II. The proposed method considers that the scatterers map is a property of the tissue; therefore, the scatterers should move according to the tissue strain. Methods First, a volume representing the target tissue is loaded. Second, parameter values, such as Young’s Modulus, scatterers density, attenuation and scattering amplitudes are inserted for each different regions of the phantom. Then, other parameters related to the ultrasound equipment, such as ultrasound frequency and number of transducer elements, are also defined in order to perform the ultrasound acquisition using Field II. Third, the size and position of the transducer and the pressures that are applied against the tissue are defined. Subsequently, FEM is executed and deformation is computed. Next, 3D linear isomorphism is performed to displace the scatterers according to the deformation. Finally, Field II is carried out to generate the non-deformed and deformed ultrasound data. Results The framework is evaluated by comparing strain values obtained the numerical simulation and from the physical phantom from CIRS. The mean difference between both phantoms is lesser than 10%. Conclusion The acoustic and deformation outcomes are similar to those obtained using a physical phantom. This framework led to a tool, which is available online and free of charges for educational and research purposes.

Resumo em Inglês:

Abstract Introduction Cardiovascular diseases (CVD) have been the focus of research in recent years due to its high mortality rate. It is estimated that 17.5 million people died of CVD in 2012, from which 7.4 million were due to coronary heart disease (CHD). In order to monitor CHD patients and avoid waste of specialists' time, this study proposes the development of a method that segments the area contained by stent struts from Frequency Domain Intravascular Optical Coherence Tomography (the latest technology to view vessels internally) of coronary arteries. Methods The novelty of this study is to find areas comprised by stent struts using two optimal strategies that are robust even with false positives and false negatives detection of stent struts. The first one uses an ellipse fitting algorithm and the other uses a cylinder fitting algorithm. Results Both strategies obtained similar accuracy results close to 98% of true positives, but the cylinder technique showed a run time of at least 50 times higher than the ellipse technique. Conclusion The methods were executed on 443 images with different characteristics showing robustness and usefulness in the medical area.

Resumo em Inglês:

Abstract Introduction Arterial Blood Pressure is a significant indicator of the current health condition of an individual. The correct detection of hypertension is essential, where this health problem is considered as one of the greatest health risks factors that affect the heart and circulatory system. This paper presents the importance of the application of metrological criteria for the diagnosis of hypertension using a sphygmomanometer aneroid. Methods 72 mechanical aneroid sphygmomanometers were calibrated using a standard manometer and the indication error, hysteresis, air leakage and rapid exhaust were determined; readings of these sphygmomanometers were compared to a properly calibrated and adjusted aneroid sphygmomanometer to carry out pressure measurements as those made during the hypertension diagnosis; the uncertainty of measurement associated with the sphygmomanometers calibration, and pressure values was assessed according to the recommendations of the Guide to the Expression of Uncertainty in Measurement, defined by the Joint Committee for Guides in Metrology. Results The results obtained have shown that about 61% of the evaluated aneroid sphygmomanometers did not meet the specifications. The variable that most contributed to the final calibration uncertainty was the hysteresis of the standard manometer, with 53% of contribution, followed by the sphygmomanometer resolution with 27%. Conclusion The periodic verifications are essential to evaluate the performance of these devices. It was shown that uncertainty of measurement influences the final diagnosis of hypertension and the application of metrological criteria can increase the reliability of the final diagnosis.

Resumo em Inglês:

Abstract Introduction Functional magnetic resonance imaging (fMRI) is a non-invasive technique that allows the detection of specific cerebral functions in humans based on hemodynamic changes. The contrast changes are about 5%, making visual inspection impossible. Thus, statistic strategies are applied to infer which brain region is engaged in a task. However, the traditional methods like general linear model and cross-correlation utilize voxel-wise calculation, introducing a lot of false-positive data. So, in this work we tested post-processing cluster algorithms to diminish the false-positives. Methods In this study, three clustering algorithms (the hierarchical cluster, k-means and self-organizing maps) were tested and compared for false-positive removal in the post-processing of cross-correlation analyses. Results Our results showed that the hierarchical cluster presented the best performance to remove the false positives in fMRI, being 2.3 times more accurate than k-means, and 1.9 times more accurate than self-organizing maps. Conclusion The hierarchical cluster presented the best performance in false-positive removal because it uses the inconsistency coefficient threshold, while k-means and self-organizing maps utilize a priori cluster number (centroids and neurons number); thus, the hierarchical cluster avoids clustering scattered voxels, as the inconsistency coefficient threshold allows only the voxels to be clustered that are at a minimum distance to some cluster.

Resumo em Inglês:

Abstract Introduction Therapeutic ultrasound (TUS) is a widespread modality in physiotherapy, and the water bag technique is a coupling method employed in the presence of anatomical irregularities in the treatment area. The aim of the present study is to evaluate the acoustic attenuation of the water bag and its effectiveness as a TUS coupling agent. Methods The rated output powers (ROPs) of the TUS equipment were evaluated based on IEC 61689. Then, a radiation force balance was used to measure ROP with and without a water bag (latex and nitrile gloves filled with deionized water) between a TUS transducer and the cone-shaped target of the balance. Each experiment was performed five times for each nominal power (0.5, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, and 7.0 W) and in the following configurations: without the water bag (A), with nitrile gloves and with (B) and without (C) a height controller, and latex gloves with (D) and without (E) height controller. ROPs obtained in different media were compared. Results The highest relative error of ROP was 16.72% for 0.5 W. Although the power values of the equipment were within the range recommended by IEC, there was a significant difference between the ROP values measured with A and with B, C and D. Conclusion As intensity differences below 0.5 W/cm2 are considered clinically not relevant, conditions A, B, C, D, or E can be used interchangeably.

Resumo em Inglês:

Abstract Introduction Rheumatoid arthritis (RA) is a chronic, multisystem disease that involves synovial inflammation, leading to deformities, like finger ulnar deviation, pain and functional difficulties. The conservative treatment comprises orthoses, features added to the body that aims to correct deformity, reduce pain and improve functionality. In the market there are few kinetic/mobile orthosis models for correction of ulnar deviation in the fingers. However, users usually complain about increased palmar volume, presence of pressure points and functional loss, demonstrating the necessity to develop more effective orthoses. In this paper we introduce an innovative concept, of an original and articulate dynamic/kinetics orthosis, which aims to correct this finger deformity and encourage functionality. Methods Methodological procedures were divided into: Need Recognition; Specification Concept; Prototype and Validation. This paper deals with the last two stages of this research. Results A virtual orthosis prototype using CAD Solid Edge Insight™ was proposed. The orthosis developed consisted of 10 pieces, made of metal and resin with carbon fiber. Conclusion After virtual movement simulation, it was verified that the prototype allows for wrist and finger flexion/extension, the possibility of bilateral use, and provids ulnar deviation correction for the fingers. The final product is innovative and is easy to put on/off; volunteers claimed that the new prototype was satisfactory in terms of deformity correction.

Resumo em Inglês:

Abstract Introduction Ozonization is an alternative sterilization process for heat-sensitive medical devices. However, the side effects of this process on packaging materials should be verified. Methods Four types of commercial disposable packaging for medical devices were evaluated after undergoing ozone sterilization: crepe paper sheet, non-woven fabric sheet (SMS), medical grade paper-plastic pouch and Tyvec©-plastic pouch. For each material, the gas penetration through the microbiological barrier was measured. Other packaging properties, such as chemical composition, color, tactile and mechanical resistance, were also evaluated after sterilization, by using characterization techniques, namely microbiological indicators, infrared spectroscopy, tensile test and optical microscopy. Results All commercial disposable packaging showed good ozone penetration. Crepe paper and SMS were chemically and mechanically modified by ozone, while Tyvec© only suffered mechanical modification. Paper-plastic pouch was the packaging material which just experienced an acceptable reduction in tensile resistance, showing no variations on chemical or visual properties. Conclusion The results suggest that medical grade paper-plastic pouch is the most appropriate disposable medical device packaging to be sterilized by ozone when compared to other materials.

Resumo em Inglês:

Abstract Introduction Breast cancer is the first leading cause of death for women in Brazil as well as in most countries in the world. Due to the relation between the breast density and the risk of breast cancer, in medical practice, the breast density classification is merely visual and dependent on professional experience, making this task very subjective. The purpose of this paper is to investigate image features based on histograms and Haralick texture descriptors so as to separate mammographic images into categories of breast density using an Artificial Neural Network. Methods We used 307 mammographic images from the INbreast digital database, extracting histogram features and texture descriptors of all mammograms and selecting them with the K-means technique. Then, these groups of selected features were used as inputs of an Artificial Neural Network to classify the images automatically into the four categories reported by radiologists. Results An average accuracy of 92.9% was obtained in a few tests using only some of the Haralick texture descriptors. Also, the accuracy rate increased to 98.95% when texture descriptors were mixed with some features based on a histogram. Conclusion Texture descriptors have proven to be better than gray levels features at differentiating the breast densities in mammographic images. From this paper, it was possible to automate the feature selection and the classification with acceptable error rates since the extraction of the features is suitable to the characteristics of the images involving the problem.

Resumo em Inglês:

Abstract Introduction Sign language is a collection of gestures, postures, movements, and facial expressions used by deaf people. The Brazilian sign language is Libras. The use of Libras has been increased among the deaf communities, but is still not disseminated outside this community. Sign language recognition is a field of research, which intends to help the deaf community communication with non-hearing-impaired people. In this context, this paper describes a new method for recognizing hand configurations of Libras - using depth maps obtained with a Kinect® sensor. Methods The proposed method comprises three phases: hand segmentation, feature extraction, and classification. The segmentation phase is independent from the background and depends only on pixel value. The feature extraction process is independent from rotation and translation. The features are extracted employing two techniques: (2D)2LDA and (2D)2PCA. The classification employs two classifiers: a novelty classifier and a KNN classifier. A robust database is constructed for classifier evaluation, with 12,200 images of Libras and 200 gestures of each hand configuration. Results The best accuracy obtained was 96.31%. Conclusion The best gesture recognition accuracy obtained is much higher than the studies previously published. It must be emphasized that this recognition rate is obtained for different conditions of hand rotation and proximity of the depth camera, and with a depth camera resolution of only 640×480 pixels. This performance must be also credited to the feature extraction technique, and to the size standardization and normalization processes used previously to feature extraction step.