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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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Imaging subjects.(a, b) Dot and vessel phantoms printed onto transparent overhead projector film using a standard black and white laser printer. (c) Perfused and excised mouse brain. Left side: front of the brain. Right side: rear of the brain (cerebellum). (d) In vivo subcutaneous mouse tumor model. Notice the dimple at the bottom of the plastic tray (indicated by the black arrow), which contains a small amount of coupling fluid (water), and is used to help position the subcutaneous tumor. The diameter of the dimple is 15 mm.
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pone.0152597.g004: Imaging subjects.(a, b) Dot and vessel phantoms printed onto transparent overhead projector film using a standard black and white laser printer. (c) Perfused and excised mouse brain. Left side: front of the brain. Right side: rear of the brain (cerebellum). (d) In vivo subcutaneous mouse tumor model. Notice the dimple at the bottom of the plastic tray (indicated by the black arrow), which contains a small amount of coupling fluid (water), and is used to help position the subcutaneous tumor. The diameter of the dimple is 15 mm.

Mentions: In this study, the imaging subjects used were an approximately spherical pencil lead point (0.3 mm in diameter), two physical phantoms, an in vivo subcutaneous mouse tumor model and a perfused and excised mouse brain. All animal work was conducted in accordance with the guidelines of and approved by the Administrative Panel on Laboratory Animal Care at Stanford University. Tumors were allowed to grow up to 1000 mm3. Animals were euthanized if they showed hunched posture, unkempt coat, or change in body weight more than 20% of baseline. No animals died during any point of the scanning procedures. Animals were given access to standard water and diet ad libitum and housed no more than 5 per cage. Animals were housed in a negative pressure vivarium with standard 12 hour light/dark cycles. The phantoms were produced by printing a digital design onto a transparent overhead projector film using a standard black and white laser printer (Xerox Phaser 3600 PS). The print resolution was 600 × 600 dpi, and the ink used was from a standard Xerox Phaser 3600 PS black and white toner cartridge. The thickness and material of the transparency were 0.1 mm and cellulose acetate, respectively. The designs are shown in Fig 4(a) and 4(b), where the white straws used to lower the phantoms into the water are also shown. The dots were 0.6 mm in diameter. The maximum width of the vessel phantom was 0.4 mm. The digital design of the vessel phantom was obtained from the k-Wave Toolbox for Matlab [46].


Comparison of Deconvolution Filters for Photoacoustic Tomography.

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

Imaging subjects.(a, b) Dot and vessel phantoms printed onto transparent overhead projector film using a standard black and white laser printer. (c) Perfused and excised mouse brain. Left side: front of the brain. Right side: rear of the brain (cerebellum). (d) In vivo subcutaneous mouse tumor model. Notice the dimple at the bottom of the plastic tray (indicated by the black arrow), which contains a small amount of coupling fluid (water), and is used to help position the subcutaneous tumor. The diameter of the dimple is 15 mm.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0152597.g004: Imaging subjects.(a, b) Dot and vessel phantoms printed onto transparent overhead projector film using a standard black and white laser printer. (c) Perfused and excised mouse brain. Left side: front of the brain. Right side: rear of the brain (cerebellum). (d) In vivo subcutaneous mouse tumor model. Notice the dimple at the bottom of the plastic tray (indicated by the black arrow), which contains a small amount of coupling fluid (water), and is used to help position the subcutaneous tumor. The diameter of the dimple is 15 mm.
Mentions: In this study, the imaging subjects used were an approximately spherical pencil lead point (0.3 mm in diameter), two physical phantoms, an in vivo subcutaneous mouse tumor model and a perfused and excised mouse brain. All animal work was conducted in accordance with the guidelines of and approved by the Administrative Panel on Laboratory Animal Care at Stanford University. Tumors were allowed to grow up to 1000 mm3. Animals were euthanized if they showed hunched posture, unkempt coat, or change in body weight more than 20% of baseline. No animals died during any point of the scanning procedures. Animals were given access to standard water and diet ad libitum and housed no more than 5 per cage. Animals were housed in a negative pressure vivarium with standard 12 hour light/dark cycles. The phantoms were produced by printing a digital design onto a transparent overhead projector film using a standard black and white laser printer (Xerox Phaser 3600 PS). The print resolution was 600 × 600 dpi, and the ink used was from a standard Xerox Phaser 3600 PS black and white toner cartridge. The thickness and material of the transparency were 0.1 mm and cellulose acetate, respectively. The designs are shown in Fig 4(a) and 4(b), where the white straws used to lower the phantoms into the water are also shown. The dots were 0.6 mm in diameter. The maximum width of the vessel phantom was 0.4 mm. The digital design of the vessel phantom was obtained from the k-Wave Toolbox for Matlab [46].

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