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Ultrason Imaging ; 41(1): 17-34, 2019 01.
Artigo em Inglês | MEDLINE | ID: mdl-30239291

RESUMO

We describe the concept of a new imaging modality based on the tracking and dynamic modeling of local intensity changes (ICs) observed in conventional ultrasound images collected during a medium-temperature change. We computed the pixel-by-pixel IC from averaged B-mode images that exhibited different behaviors with varying temperature resulting from changes in the speed of sound, which consequently induce changes in the backscattered energy. Moreover, for each pixel, a first-order polynomial model was adjusted to the different temperature-dependent ICs. The representation of the polynomial angular parameter in 2D pixel space was used to obtain a parametric image. The results obtained by simulations and with real B-mode images indicated that this new ultrasound imaging modality was able to enhance the contrast and highlight structures that were poorly visible or even undetected in conventional images. A temperature change of 3°C was found to be sufficient to generate appropriate images with the proposed method. In addition, if a temperature change of 6°C was considered, the thermal dose, measured as the cumulative number of equivalent minutes at 43°C (CEM43°C), was 2.4 CEM43°C, which is a value that is considered safe according to the literature. We provide a proof-of-concept of a new imaging modality that opens new opportunities for the enhancement of ultrasound images and consequently contributes to improvements in ultrasound-based diagnoses. Our approach is based on images returned by commercial ultrasound scanners. Therefore, it can be implemented in any ultrasound system and is independent of specific ultrasound hardware and software data acquisition characteristics.


Assuntos
Aumento da Imagem/métodos , Processamento de Imagem Assistida por Computador/métodos , Temperatura , Ultrassonografia/métodos , Algoritmos , Animais , Simulação por Computador , Estudos de Viabilidade , Modelos Animais , Modelos Estatísticos , Suínos
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