MARCO ANTONIO GUTIERREZ
Projetos de Pesquisa
Unidades Organizacionais
Instituto do Coração, Hospital das Clínicas, Faculdade de Medicina
LIM/65, Hospital das Clínicas, Faculdade de Medicina - Líder
LIM/65, Hospital das Clínicas, Faculdade de Medicina - Líder
5 resultados
Resultados de Busca
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- Directional analysis of cardiac motion field from gated fluorodeoxyglucose PET images using the Discrete Helmholtz Hodge Decomposition(2018) SIMS, J. A.; GIORGI, M. C.; OLIVEIRA, M. A.; MENEGHETTI, J. C.; GUTIERREZ, M. A.Objectives: Extract directional information related to left ventricular (LV) rotation and torsion from a 4D PET motion field using the Discrete Helmholtz Hodge Decomposition (DHHD). Materials and methods: Synthetic motion fields were created using superposition of rotational and radial field components and cardiac fields produced using optical flow from a control and patient image. These were decomposed into curl-free (CF) and divergence-free (DF) components using the DHHD. Results: Synthetic radial components were present in the CF field and synthetic rotational components in the DF field, with each retaining its center position, direction of motion and diameter after decomposition. Direction of rotation at apex and base for the control field were in opposite directions during systole, reversing during diastole. The patient DF field had little overall rotation with several small rotators. Conclusions: The decomposition of the LV motion field into directional components could assist quantification of LV torsion, but further processing stages seem necessary.
- Cerebral blood flow changes during intermittent acute hypoxia in patients with heart failure(2018) MANSUR, Antonio P.; ALVARENGA, Glaura Souza; KOPEL, Liliane; GUTIERREZ, Marco Antonio; CONSOLIM-COLOMBO, Fernanda Marciano; HAJJAR, Ludhmila Abrahao; LAGE, Silvia GelasObjective: Heart failure (HF) is associated with intermittent hypoxia, and the effects of this hypoxia on the cardiovascular system are not well understood. This study was performed to compare the effects of acute hypoxia (10% oxygen) between patients with and without HF. Methods: Fourteen patients with chronic HF and 17 matched control subjects were enrolled. Carotid artery changes were examined during the first period of hypoxia, and brachial artery changes were examined during the second period of hypoxia. Data were collected at baseline and after 2 and 4 minutes of hypoxia. Norepinephrine, epinephrine, dopamine, and renin were measured at baseline and after 4 minutes hypoxia. Results: The carotid blood flow, carotid systolic diameter, and carotid diastolic diameter increased and the carotid resistance decreased in patients with HF. Hypoxia did not change the carotid compliance, distensibility, brachial artery blood flow and diameter, or concentrations of sympathomimetic amines in patients with HF, but hypoxia increased the norepinephrine level in the control group. Hypoxia increased minute ventilation and decreased the oxygen saturation and end-tidal carbon dioxide concentration in both groups. Conclusion: Hypoxia-induced changes in the carotid artery suggest an intensification of compensatory mechanisms for preservation of cerebral blood flow in patients with HF.
conferenceObject Lumen Segmentation in Optical Coherence Tomography Images using Convolutional Neural Network(2018) MIYAGAWA, M.; COSTA, M. G. F.; GUTIERREZ, M. A.; COSTA, J. P. G. F.; COSTA FILHO, C. F. F.Lumen segmentation in Optical Coherence Tomography (OCT) images is a very important step to analyze points of interest that may help on atherosclerosis diagnostic and treatment. Past studies use many different methods to segment the lumen in IVOCT images, like level set, morphological reconstruction, Markov random fields, and Otsu binarization. Despite Convolutional Neural Networks (CNN) have shown promising results in the image processing area, we did not identify, in the literature, works applying CNN in IVOCT images. In this paper, we present the lumen segmentation using CNN. We evaluated three different CNN architectures. The CNNs were evaluated using three versions from the image dataset, differing from each other by image size (768x768 pixels and 192x192 pixels), and by coordinate system representation (Cartesian and polar). The best results, Accuracy, Dice index and Jaccard index of over 99%, 98% and 97%, respectively, were obtained with the smallest size images represented by polar coordinate system.- Development of a System Mobile-based to Assist Asthma Self-Management(2018) SILVA, Thales A.; COSTA, Marly G. F.; STELMACH, Rafael; BLEY, Peter K.; GUTIERREZ, Marco A.; COSTA FILHO, Cicero F. F.Self-management is a major factor in the treatment of asthma and contributes to reduce morbidity in adults and children. However, adherence to self-management depends on a number of factors, including literacy and understanding of disease and health concepts. This paper proposes a system based on the use of mobile devices in order to provide tools to help with adherence to self-management, in addition to propose a narrowing between doctor and patient communication. The proposed system consists of a mobile application for the Android platform, a WEB application and online features of Firebase. In the usability evaluation of the system, most users (82%) rated it as useful and would use the system regularly to support the self-management of asthma.
- Coronary calcification identification in Optical Coherence Tomography using convolutional neural networks(2018) OLIVEIRA, Dario A. B.; MACEDO, Maysa M. G.; NICZ, Pedro; CAMPOS, Carlos; LEMOS, Pedro; GUTIERREZ, Marco. A.Intravascular optical coherence tomography (IOCT) is a modality that provides sufficient resolution for very accurate visualization of localized cardiovascular conditions, such as coronary artery calcification (CAC). CAC quantification in IOCT images is still performed mostly manually, which is time consuming, considering that each IOCT exam has more than two hundred 2D slices. An automated method for CAC detection in IOCT would add valuable information for clinicians when treating patients with coronary atherosclerosis. In this context, we propose an approach that uses a fully connected neural network (FCNN) for CAC detection in IOCT images using a small training dataset. In our approach, we transform the input image to polar coordinate transformation using as reference the centroid from the lumen segmentation, that restricts the variability in CAC spatial position, which we proved to be beneficial for the CNN training with few training data. We analyzed 51 slices from in-vivo human coronaries and the method achieved 63.6% sensitivity and 99.8% specificity for segmenting CAC. Our results demonstrate that it is possible to successfully detect and segment calcific plaques in IOCT images using FCNNs.