The generalized contrast-to-noise ratio (gCNR) is a relatively new image quality metric designed to assess the probability of lesion detectability in ultrasound images. Although gCNR was initially demonstrated with ultrasound images, the metric is theoretically applicable to multiple types of medical images. In this paper, the applicability of gCNR to photoacoustic images is investigated. The gCNR was computed for both simulated and experimental photoacoustic images generated by amplitude-based (i.e., delay-and-sum) and coherence-based (i.e., short-lag spatial coherence) beamformers. These gCNR measurements were compared to three more traditional image quality metrics (i.e., contrast, contrast-to-noise ratio, and signal-to-noise ratio) applied to the same datasets. An increase in qualitative target visibility generally corresponded with increased gCNR. In addition, gCNR magnitude was more directly related to the separability of photoacoustic signals from their background, which degraded with the presence of limited bandwidth artifacts and increased levels of channel noise. At high gCNR values (i.e., 0.95-1), contrast, contrast-to-noise ratio, and signal-to-noise ratio varied by up to 23.7-56.2 dB, 2.0-3.4, and 26.5-7.6×1020, respectively, for simulated, experimental phantom, andin vivodata. Therefore, these traditional metrics can experience large variations when a target is fully detectable, and additional increases in these values would have no impact on photoacoustic target detectability. In addition, gCNR is robust to changes in traditional metrics introduced by applying a minimum threshold to image amplitudes. In tandem with other photoacoustic image quality metrics and with a defined range of 0 to 1, gCNR has promising potential to provide additional insight, particularly when designing new beamformers and image formation techniques and when reporting quantitative performance without an opportunity to qualitatively assess corresponding images (e.g., in text-only abstracts).
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Photoacoustic tomography of fingerprint and underlying vasculature for improved biometric identification
Abstract Capitalizing on the photoacoustic effect, we developed a new fingerprint sensing system that can reveal both fingerprints and underlying vascular structures at a high spatial resolution. Our system is built on a 15 MHz linear transducer array, a research ultrasound system, and a 532-nm pulsed laser. A 3D image was obtained by scanning the linear array over the fingertip. The acquired fingerprint images strongly agreed with the images acquired from ultrasound. Additional experiments were also conducted to investigate the effect of acoustic coupling. We discovered that high-quality fingerprint and vessel images can be acquired from both wet and dry fingers using our photoacoustic system. The reduced subdermal features in dry coupling can be enhanced through post-processing. Compared to existing fingerprint scanners, the photoacoustic approach provides a higher quality 3D image of the fingerprint, as well as unique subdermal vasculature structures, making the system almost impossible to counterfeit.
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- Award ID(s):
- 1822190
- PAR ID:
- 10362729
- Date Published:
- Journal Name:
- Scientific Reports
- Volume:
- 11
- Issue:
- 1
- ISSN:
- 2045-2322
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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