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Processamento de imagens contilográficas, aplicado à reorientação 3D, para avaliação de Perfusão Miocárdica no diagnóstico da Doença Arterial Coronariana. / Contigraphical image processing, applied to 3D reorientation, for evaluation of Myocardial Perfusion in the diagnosis of Coronary Artery Disease.SOUZA, Ianna Duarte Kobayashi de. 07 August 2018 (has links)
Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-08-07T19:46:16Z
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IANNA DUARTE KOBAYASHI DE SOUZA - DISSERTAÇÃO PPGCC 2012..PDF: 9922437 bytes, checksum: d5cbecd7f839d5802dab4ed420e1665b (MD5) / Made available in DSpace on 2018-08-07T19:46:16Z (GMT). No. of bitstreams: 1
IANNA DUARTE KOBAYASHI DE SOUZA - DISSERTAÇÃO PPGCC 2012..PDF: 9922437 bytes, checksum: d5cbecd7f839d5802dab4ed420e1665b (MD5)
Previous issue date: 2012-02-29 / O crescimento da incidência da doença arterial coronariana, que atinge parte da população mundial, tem intensificado avanços na área da medicina nuclear, como forma de prevenção e de diagnóstico dessa doença. A cintilografia do miocárdio com técnica SPECT (Single Photon Emission Computed Tomography), associada ao eletrocardiograma, permite a avaliação tanto da funcionalidade quanto da perfusão do
músculo cardíaco. Este estudo tem como objetivo principal aplicar técnicas de processamento digital de imagens para segmentar e reorientar automaticamente as imagens 3D de pacientes doentes, geradas por uma gamma camera. Os resultados obtidos foram comparados com os resultados produzidos pela técnica manual e
comprovaram a eficácia do método automático proposto. / The increase in incidence of coronary artery disease, which affects part of the world population, has intensified advances in nuclear medicine as a means of prevention and diagnosis of this disease. The myocardial scintigraphy technique SPECT (Single Photon Emission Computed Tomography), associated with the electrocardiogram, enables evaluating both function and perfusion of the heart muscle. The main objective of
this study is to apply techniques of digital image processing to segment and reorient automatically the 3D images of sick patients, generated by a gamma camera. The results obtained were compared to those ones produced by a manual technique and the effectiveness of the proposed automatic method was confirmed.
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