ANTONILDES NASCIMENTO ASSUNCAO JUNIOR
Projetos de Pesquisa
Unidades Organizacionais
Instituto do Coração, Hospital das Clínicas, Faculdade de Medicina - Médico
LIM/65, Hospital das Clínicas, Faculdade de Medicina
LIM/65, Hospital das Clínicas, Faculdade de Medicina
6 resultados
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conferenceObject Long-Term Prognosticvalue of Coronary Computed Tomography Scores to Predict Cardiovascular Events: The CORE64 and CORE320 Studies(2018) LIMA, Thais P.; ASSUNCAO JR., Antonildes N.; BITTENCOURT, Marcio S.; LIBERATO, Gabriela; LIMA, Joao A.; ROCHITTE, Carlos E.- U-Net Neural Network for Locating Midpoint of Insertion Zone of Transcatheter Aortic Valves in CTA Images(2021) MINEO, Eduardo; ASSUNCAO-JR, Antonildes N.; MORAIS, Thamara C.; CAMARA, Sergio F.; RIBEIRO, Henrique B.; SIMS, John A.; NOMURA, Cesar H.Identifying the insertion zone of transcatheter heart valves can be time-consuming and suffers from variability and reproducibility problems. We present a deep leaning approach in CTA images to locate the midpoint of the insertion zone. A U-Net neural network is implemented to automatically segment the aortic valve on axial projection. The insertion zone midpoint is calculated based on the range of slices with the more concentrated area of activated pixels. We found a very low systematic error with a median computed error of 0.38mm and interquartile range of 0.15 - 0.75mm. The proposed model was shown to be a robust and powerful tool to automatically locate the insertion zone midpoint and we believe it will play a critical role on automated assessment of aortic stenosis.
conferenceObject Coronary Perivascular Fat Attenuation Index in Heterozygous Familial Hypercholesterolemia(2019) MINAME, Marcio H.; BERCHT, Andrea M.; MORAIS, Thamara; ASSUNCAO JR., Antonildes; SANTOS, Raul D.; NOMURA, Cesar Higa- A combined deep-learning approach to fully automatic left ventricle segmentation in cardiac magnetic resonance imaging(2019) MORENO, Ramon A.; REBELO, Marina F. S. de Sa; CARVALHO, Talles; ASSUNCAO-JR, Antonildes N.; JR, Roberto N. Dantas; VAL, Renata do; MARIN, Angela S.; BORDIGNOM, Adriano; NOMURA, Cesar H.; GUTIERREZ, Marco A.In clinical practice, cardiac magnetic resonance imaging (CMR) is considered the gold-standard imaging modality for the evaluation of function and structure of the left ventricle (LV). However, the quantification of LV parameters in all frames, even when performed by experienced radiologists, is very time consuming mainly due to the inhomogeneity of cardiac structures within each image, the variability of the cardiac structures across subjects and the complicated global/regional temporal deformation of the myocardium during the cardiac cycle. In this work, we employed a combination of two convolutional neural networks (CNN) to develop a fully automatic LV segmentation method for Short Axis CMR datasets. The first CNN defines the region of interest (ROI) of the cardiac chambers based on You Only Look Once (YOLO) network. The output of YOLO net is used to filter the image and feed the second CNN, based on U-Net network, which segments the myocardium and the blood pool. The method was validated in CMR exams of 59 individuals from an institutional clinical protocol. Segmentation results, evaluated by metrics Percentage of Good Contours, Dice Index and Average Perpendicular distance, were 98,59% +/- 4,28%, 0,93 +/- 0,06 and 0,72 mm +/- 0,62 mm, respectively, for the LV epicardium, and 94,98% +/- 14,04%, 0,86 +/- 0,13 and 1,19 mm +/- 1,29 mm, respectively, for the LV endocardium. The combination of two CNNs demonstrated good performance in terms of the evaluated metrics when compared to literature results.
conferenceObject HIGH SENSITIVITY CARDIAC TROPONIN I CHANGES RELATED WITH T1 MAPPING IN PATIENTS WITH CHRONIC ISCHAEMIC HEART DISEASE WITHOUT LATE ENHANCEMENT GADOLINIUM BY CRM(2015) SEGRE, Carlos; ASSUNCAO JUNIOR, Antonildes Nascimento; NOMURA, Cesar; VILLA, Alexandre; STRUNZ, Celia; REZENDE, Paulo; PARGA, Jose; TAKIUTI, Myrthes Emy; HUEB, Whady; RAMIRES, Jose; KALIL-FILHO, Roberto- Automated computed tomography lung densitometry in bronchiectasis patients(2020) SAWAMURA, Marcio Yamada; ATHANAZIO, Rodrigo Abensur; NUCCI, Maria Cecilia Nieves Teixeira Maiorano De; RACHED, Samia Zahi; CUKIER, Alberto; CAVALHO-PINTO, Regina Maria; STELMACH, Rafael; ASSUNCAO JUNIOR, Antonildes Nascimento; TAKAHASHI, Marcelo Straus; NOMURA, Cesar Higa