https://scholars.lib.ntu.edu.tw/handle/123456789/607025
標題: | A rapid denoised contrast enhancement method digitally mimicking an adaptive illumination in submicron-resolution neuronal imaging | 作者: | Borah B.J Sun C.-K. CHI-KUANG SUN |
關鍵字: | Biological sciences research methodologies;Cell biology;Neuroscience;Optical imaging | 公開日期: | 2022 | 卷: | 25 | 期: | 2 | 來源出版物: | iScience | 摘要: | Optical neuronal imaging often shows ultrafine structures, such as a nerve fiber, coexisting with ultrabright structures, such as a soma with a substantially higher fluorescence-protein concentration. Owing to experimental and environmental factors, a laser-scanning multiphoton optical microscope (MPM) often encounters a high-frequency background noise that might contaminate such weak-intensity ultrafine neuronal structures. A straightforward contrast enhancement often leads to the saturation of the brighter ones, and might further amplify the high-frequency background noise. We report a digital approach called rapid denoised contrast enhancement (DCE), which digitally mimics a hardware-based adaptive/controlled illumination technique by means of digitally optimizing the signal strengths and hence the visibility of such weak-intensity structures while mostly preventing the saturation of the brightest ones. With large field-of-view (FOV) two-photon excitation fluorescence (TPEF) neuronal imaging, we validate the effectiveness of DCE over state-of-the-art digital image processing algorithms. With compute-unified-device-architecture (CUDA)-acceleration, a real-time DCE is further enabled with a reduced time complexity. ? 2022 The Author(s) |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123907839&doi=10.1016%2fj.isci.2022.103773&partnerID=40&md5=6d3ae929c311b1b17cb1b64545bf50ab https://scholars.lib.ntu.edu.tw/handle/123456789/607025 |
ISSN: | 25890042 | DOI: | 10.1016/j.isci.2022.103773 |
顯示於: | 電機工程學系 |
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