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Comparison of Deconvolution Filters for Photoacoustic Tomography.

Van de Sompel D, Sasportas LS, Jokerst JV, Gambhir SS - PLoS ONE (2016)

Bottom Line: It was found that the Tikhonov filter yielded the most accurate balance of lower and higher frequency content (as measured by comparing the spectra of deconvolved impulse response signals to the ideal flat frequency spectrum), achieved a competitive image resolution and contrast-to-noise ratio, and yielded the greatest robustness to noise.In addition, its robustness to noise was poorer than that of the Tikhonov filter.Overall, the Tikhonov filter was deemed to produce the most desirable image reconstructions.

View Article: PubMed Central - PubMed

Affiliation: Molecular Imaging Program at Stanford (MIPS), Stanford University School of Medicine, Stanford University, Stanford, CA 94305, United States of America.

ABSTRACT
In this work, we compare the merits of three temporal data deconvolution methods for use in the filtered backprojection algorithm for photoacoustic tomography (PAT). We evaluate the standard Fourier division technique, the Wiener deconvolution filter, and a Tikhonov L-2 norm regularized matrix inversion method. Our experiments were carried out on subjects of various appearances, namely a pencil lead, two man-made phantoms, an in vivo subcutaneous mouse tumor model, and a perfused and excised mouse brain. All subjects were scanned using an imaging system with a rotatable hemispherical bowl, into which 128 ultrasound transducer elements were embedded in a spiral pattern. We characterized the frequency response of each deconvolution method, compared the final image quality achieved by each deconvolution technique, and evaluated each method's robustness to noise. The frequency response was quantified by measuring the accuracy with which each filter recovered the ideal flat frequency spectrum of an experimentally measured impulse response. Image quality under the various scenarios was quantified by computing noise versus resolution curves for a point source phantom, as well as the full width at half maximum (FWHM) and contrast-to-noise ratio (CNR) of selected image features such as dots and linear structures in additional imaging subjects. It was found that the Tikhonov filter yielded the most accurate balance of lower and higher frequency content (as measured by comparing the spectra of deconvolved impulse response signals to the ideal flat frequency spectrum), achieved a competitive image resolution and contrast-to-noise ratio, and yielded the greatest robustness to noise. While the Wiener filter achieved a similar image resolution, it tended to underrepresent the lower frequency content of the deconvolved signals, and hence of the reconstructed images after backprojection. In addition, its robustness to noise was poorer than that of the Tikhonov filter. The performance of the Fourier filter was found to be the poorest of all three methods, based on the reconstructed images' lowest resolution (blurriest appearance), generally lowest contrast-to-noise ratio, and lowest robustness to noise. Overall, the Tikhonov filter was deemed to produce the most desirable image reconstructions.

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Representative slices through the perfused and excised mouse brain.
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pone.0152597.g005: Representative slices through the perfused and excised mouse brain.

Mentions: Lastly, the mouse brain perfusion and excision was performed as follows. After placing the mouse under deep anesthesia, the animal’s chest and abdomen were exposed by making a surgical cut along the midline. The frontal rib cage was cut, exposing the pericardium. A large gauge needle (18 gauge) connected to a syringe by a long PE tube was inserted into the left ventricle of the heart. The inferior vena cava was severed with scissors to allow the blood, saline and fixative to leave the body during perfusion. Using a syringe pump, the mouse was perfused with 20 mL of saline for 5–10 min followed by 20 mL of 10% formalin fixative solution. After perfusion, a craniotomy was performed and the brain was excised carefully and stored in 10% formalin. The perfused and excised mouse brain is shown in Fig 4(c). A collection of representative slices through the mouse brain, obtained after the photoacoustic scan, is shown in Fig 5.


Comparison of Deconvolution Filters for Photoacoustic Tomography.

Van de Sompel D, Sasportas LS, Jokerst JV, Gambhir SS - PLoS ONE (2016)

Representative slices through the perfused and excised mouse brain.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4816281&req=5

pone.0152597.g005: Representative slices through the perfused and excised mouse brain.
Mentions: Lastly, the mouse brain perfusion and excision was performed as follows. After placing the mouse under deep anesthesia, the animal’s chest and abdomen were exposed by making a surgical cut along the midline. The frontal rib cage was cut, exposing the pericardium. A large gauge needle (18 gauge) connected to a syringe by a long PE tube was inserted into the left ventricle of the heart. The inferior vena cava was severed with scissors to allow the blood, saline and fixative to leave the body during perfusion. Using a syringe pump, the mouse was perfused with 20 mL of saline for 5–10 min followed by 20 mL of 10% formalin fixative solution. After perfusion, a craniotomy was performed and the brain was excised carefully and stored in 10% formalin. The perfused and excised mouse brain is shown in Fig 4(c). A collection of representative slices through the mouse brain, obtained after the photoacoustic scan, is shown in Fig 5.

Bottom Line: It was found that the Tikhonov filter yielded the most accurate balance of lower and higher frequency content (as measured by comparing the spectra of deconvolved impulse response signals to the ideal flat frequency spectrum), achieved a competitive image resolution and contrast-to-noise ratio, and yielded the greatest robustness to noise.In addition, its robustness to noise was poorer than that of the Tikhonov filter.Overall, the Tikhonov filter was deemed to produce the most desirable image reconstructions.

View Article: PubMed Central - PubMed

Affiliation: Molecular Imaging Program at Stanford (MIPS), Stanford University School of Medicine, Stanford University, Stanford, CA 94305, United States of America.

ABSTRACT
In this work, we compare the merits of three temporal data deconvolution methods for use in the filtered backprojection algorithm for photoacoustic tomography (PAT). We evaluate the standard Fourier division technique, the Wiener deconvolution filter, and a Tikhonov L-2 norm regularized matrix inversion method. Our experiments were carried out on subjects of various appearances, namely a pencil lead, two man-made phantoms, an in vivo subcutaneous mouse tumor model, and a perfused and excised mouse brain. All subjects were scanned using an imaging system with a rotatable hemispherical bowl, into which 128 ultrasound transducer elements were embedded in a spiral pattern. We characterized the frequency response of each deconvolution method, compared the final image quality achieved by each deconvolution technique, and evaluated each method's robustness to noise. The frequency response was quantified by measuring the accuracy with which each filter recovered the ideal flat frequency spectrum of an experimentally measured impulse response. Image quality under the various scenarios was quantified by computing noise versus resolution curves for a point source phantom, as well as the full width at half maximum (FWHM) and contrast-to-noise ratio (CNR) of selected image features such as dots and linear structures in additional imaging subjects. It was found that the Tikhonov filter yielded the most accurate balance of lower and higher frequency content (as measured by comparing the spectra of deconvolved impulse response signals to the ideal flat frequency spectrum), achieved a competitive image resolution and contrast-to-noise ratio, and yielded the greatest robustness to noise. While the Wiener filter achieved a similar image resolution, it tended to underrepresent the lower frequency content of the deconvolved signals, and hence of the reconstructed images after backprojection. In addition, its robustness to noise was poorer than that of the Tikhonov filter. The performance of the Fourier filter was found to be the poorest of all three methods, based on the reconstructed images' lowest resolution (blurriest appearance), generally lowest contrast-to-noise ratio, and lowest robustness to noise. Overall, the Tikhonov filter was deemed to produce the most desirable image reconstructions.

Show MeSH
Related in: MedlinePlus