Author
Thanh Dat Le
Bio: Thanh Dat Le is an academic researcher. The author has contributed to research in topics: Engineering & Microscopy. The author has co-authored 1 publications.
Papers
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TL;DR: Wang et al. as discussed by the authors proposed a combination of filters, including an adaptive median filter, an effective filter for impulsive noise, and a nonlocal means filter, for noise removal and image quality enhancement.
Abstract: Photoacoustic microscopy has received great attention due to the benefits of the optical resolution contrast as well as its superior spatial resolution and relatively deep depth. Like other imaging modalities, photoacoustic images suffer from noise, and filtering techniques are required to remove them. To overcome the noise, we proposed a combination of filters, including an adaptive median filter, an effective filter for impulsive noise, and a nonlocal means filter, an effective filter for background noise, for noise removal and image quality enhancement. Our proposed method enhanced the signal‐to‐noise ratio by 16 dB in an in vivo study compared to the traditional image reconstruction approach and preserved the image detail with minimal blurring, which usually occurs when filtering. These experimental results verified that the proposed adaptive multistage denoising techniques could effectively improve image quality under noisy data acquisition conditions, providing a strong foundation for photoacoustic microscopy with limited laser power.
1 citations
TL;DR: The analytic results indicate the successful implementation of wide-field PAM images, realized by applying suitable methods to the mosaic PAM imaging process, compared to traditional and deep learning feature generation algorithms by estimating the processing time, the number of matches, good matching ratio, and matching efficiency.
Abstract: Mosaic imaging is a computer vision process that is used for merging multiple overlapping imaging patches into a wide-field-of-view image. To achieve a wide-field-of-view photoacoustic microscopy (PAM) image, the limitations of the scan range of PAM require a merging process, such as marking the location of patches or merging overlapping areas between adjacent images. By using the mosaic imaging process, PAM shows a larger field view of targets and preserves the quality of the spatial resolution. As an essential process in mosaic imaging, various feature generation methods have been used to estimate pairs of image locations. In this study, various feature generation algorithms were applied and analyzed using a high-resolution mouse ear PAM image dataset to achieve and optimize a mosaic imaging process for wide-field PAM imaging. We compared the performance of traditional and deep learning feature generation algorithms by estimating the processing time, the number of matches, good matching ratio, and matching efficiency. The analytic results indicate the successful implementation of wide-field PAM images, realized by applying suitable methods to the mosaic PAM imaging process.
1 citations
07 Mar 2022
03 Mar 2022
TL;DR: In this article , feature points were selected by binary decision and were merged by homography estimation for wide field-of-view (FOV) OR-PAM image generation.
Abstract: Optical resolution-photoacoustic microscopy (OR-PAM) is a microscopic system to provide optical absorption contrast in biological tissue. Currently, high-speed OR-PAM scanning faced the limitation of the millimeter-scale field of view (FOV). Without hardware updates, mosaic processing was used to generate a wide FOV PAM image by merging narrow-ranged PAM images. Using feature generation algorithms, feature points were selected by binary decision and were merged by homography estimation. In this study, the diverse feature generation algorithms were applied and compared to estimate their performances for mosaic PAM imaging. Based on the results, mosaic processing implemented with a wide-field OR-PAM system was applied.
03 Mar 2022
TL;DR: In this paper , the authors proposed using CycleGAN to generate new OR-PAM images from the original acoustic-resolution PAM images, which can reach the depth of several centimeters in biological tissue.
Abstract: Photoacoustic microscopy (PAM) is a multiscale microscopy technique with optical absorption contrast. With tight acoustic focusing, acoustic-resolution (AR-PAM) reaches the depth of several centimeters in biological tissue, but the lateral resolution is relatively poorer than optical-resolution PAM (OR-PAM). We proposed using CycleGAN to generate new OR-PAM images from the original AR-PAM images. We prepared two AR & OR-PAM datasets from leaf phantom and mouse-ear samples. After completing the CycleGAN process, we estimated the quality comparison between the original AR-PAM and the generated OR-PAM images. Finally, the results showed the ability to obtain high spatial resolution PAM images without hardware updates.
Cited by
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TL;DR: Zhang et al. as discussed by the authors adapted an optical-resolution photoacoustic microscopy (OR-PAM) to image the nail-bed microvasculature and showed that the imaging sensitivity was significantly improved by hydration pretreatment of the nail.
Abstract: Microcirculation imaging has significantly clinical value in early diagnosis and curative effect judgment of various diseases. The most superficial layer of the nailbed is rich in capillaries, which is suitable as a window on the microcirculation. However, few techniques can noninvasively observe the blood supply distribution of the nailbed, especially for high-resolution imaging of capillaries. In this study, we adapted an optical-resolution photoacoustic microscopy (OR-PAM) to image the nailbed microvasculature. The imaging sensitivity was significantly improved by hydration pretreatment of the nail. In vitro phantom experiments demonstrate that the sensitivity was improved about 3.5 times after hydration. In vivo imaging experiments of the nailbed microvasculature were conducted to further examine the enhanced sensitivity and practicability of OR-PAM. Moreover, the quantitative analysis of capillary loops showed that OR-PAM can extract the detection indicators including vascular morphology, diameter, and length, which provides a basis for clinical microcirculation detection using OR-PAM. This article is protected by copyright. All rights reserved.
03 Mar 2022
TL;DR: In this article , feature points were selected by binary decision and were merged by homography estimation for wide field-of-view (FOV) OR-PAM image generation.
Abstract: Optical resolution-photoacoustic microscopy (OR-PAM) is a microscopic system to provide optical absorption contrast in biological tissue. Currently, high-speed OR-PAM scanning faced the limitation of the millimeter-scale field of view (FOV). Without hardware updates, mosaic processing was used to generate a wide FOV PAM image by merging narrow-ranged PAM images. Using feature generation algorithms, feature points were selected by binary decision and were merged by homography estimation. In this study, the diverse feature generation algorithms were applied and compared to estimate their performances for mosaic PAM imaging. Based on the results, mosaic processing implemented with a wide-field OR-PAM system was applied.