Joint reconstruction techniques for ultrasonic attenuation imaging
Date
2024-05-08
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Pontificia Universidad Católica del Perú
Abstract
El ultrasonido cuantitativo (QUS, por sus siglas en inglés) es una modalidad de imagen
no invasiva que caracteriza numéricamente los tejidos para el diagnóstico médico. Los
estimadores QUS se basan en parámetros acústicos como la pendiente del coeficiente de
atenuación (ACS, por sus siglas en inglés). Un estudio anterior propuso eliminar el ruido
de las relaciones logarítmicas espectrales utilizando una variación total de un solo canal a
través de la frecuencia. El método espectral para estimar el ACS, conocido como diferencia logarítmica espectral (SLD, por sus siglas en inglés) no incorpora ninguna estrategia
de reconstrucción conjunta para mejorar la imagen. Por lo tanto, este trabajo propone
la integración de dos estrategias conjuntas compatibles con el marco SLD. Primero, un
enfoque de regularización conjunta denominado variación total nuclear (TNV-SLD) es
implementado, el cual combina información geométrica del ACS y el componente del coeficiente de retrodispersión (BSC, por sus siglas en inglés) para mejorar la calidad de las
imágenes, logrando mejores resultados en términos de error porcentual medio (MPE) y
relación contraste-ruido (CNR). Posteriormente, el estudio se amplía para eliminar conjuntamente los ratios logarítmicos espectrales del SLD en los canales de frecuencia. Se
propone un método conjunto multifrecuencia para aumentar la calidad de las imágenes
de atenuación. Se consideraron dos modificaciones de la variación total con base en las
normas Frobenius (TFV) y nuclear (TNV). Las métricas se compararon con dos métodos
de regularización anteriores denominados RSLD y TVSLD, basados en la variación total
de un solo canal con datos de maniquíes simulados y experimentales, y una muestra de
tejido ex vivo. Los resultados mostraron un mejor desempeño general del método TNV
para ambas estrategias, produciendo mapas ACS mejorados y extendiendo el balance entre la resolución espacial y la variabilidad de la estimación en términos de CNR con un
sesgo estable.
Quantitative Ultrasound (QUS) is a non-invasive image modality that characterizes numerically tissues for medical diagnosis. QUS estimators are based on acoustical parameters such as the attenuation coefficient slope (ACS). A previous study proposed denoising the spectral log ratios using a single channel total variation through frequency. The spectral-based method to estimate the ACS, known as Spectral Log Difference (SLD) does not incorporate any joint reconstruction strategies for image enhancement. Therefore, this work proposes the integration of two joint strategies compatible with the SLD framework. First, a joint regularization approach named the Total Nuclear Variation SLD (TNV-SLD) is implemented. It couples geometrical information of the ACS and the backscatter coefficient (BSC) component to enhance the quality of the images, achieving better results in terms of mean percentage error (MPE) and contrast-to-noise ratio (CNR). Later, the study is extended to jointly denoise the spectral log ratios of the SLD across the frequency channels. A multi-frequency joint method is proposed to increase the quality of the attenuation images. Two modifications of the total variation based on the Frobenius (TFV) and nuclear (TNV) norms were considered. Metrics were compared to two previous regularization methods labeled RSLD and TVSLD, based on the single- channel Total Variation with data from simulated and experimental phantoms, and an ex vivo tissue sample. Results showed an overall better performance of the TNV method for both strategies, yielding enhanced ACS maps and extending the trade-off between spatial resolution and variability of the estimation in terms of the CNR with a stable bias.
Quantitative Ultrasound (QUS) is a non-invasive image modality that characterizes numerically tissues for medical diagnosis. QUS estimators are based on acoustical parameters such as the attenuation coefficient slope (ACS). A previous study proposed denoising the spectral log ratios using a single channel total variation through frequency. The spectral-based method to estimate the ACS, known as Spectral Log Difference (SLD) does not incorporate any joint reconstruction strategies for image enhancement. Therefore, this work proposes the integration of two joint strategies compatible with the SLD framework. First, a joint regularization approach named the Total Nuclear Variation SLD (TNV-SLD) is implemented. It couples geometrical information of the ACS and the backscatter coefficient (BSC) component to enhance the quality of the images, achieving better results in terms of mean percentage error (MPE) and contrast-to-noise ratio (CNR). Later, the study is extended to jointly denoise the spectral log ratios of the SLD across the frequency channels. A multi-frequency joint method is proposed to increase the quality of the attenuation images. Two modifications of the total variation based on the Frobenius (TFV) and nuclear (TNV) norms were considered. Metrics were compared to two previous regularization methods labeled RSLD and TVSLD, based on the single- channel Total Variation with data from simulated and experimental phantoms, and an ex vivo tissue sample. Results showed an overall better performance of the TNV method for both strategies, yielding enhanced ACS maps and extending the trade-off between spatial resolution and variability of the estimation in terms of the CNR with a stable bias.
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Keywords
Imagen ultrasónica, Ultrasonido en medicina, Ondas ultrasónicas--Atenuación
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