Showing 1 - 16 results of 16 for search '"biological imaging"', query time: 0.09s Refine Results
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    Biological Evaluation of Platinum(II) Sulfonamido Complexes: Synthesis, Characterization, Cytotoxicity, and Biological Imaging by Charini Maladeniya, Taniya Darshani, Sameera R. Samarakoon, Frank R. Fronczek, W. M. C. Sameera, Inoka C. Perera, Theshini Perera

    Published 2022-01-01
    “…Fluorescence imaging data of both ligands and complexes revealed the potential fluorescence activity of these compounds for biological imaging. All four compounds are promising novel candidates that can be further investigated on their usage as potential anticancer agents and cancer cell imaging agents.…”
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    Potential of Black Phosphorus in Immune-Based Therapeutic Strategies by Wenjuan Dong, Hu Wang, Hailin Liu, Chunqiao Zhou, Xuelin Zhang, Song Wang, Lin He

    Published 2022-01-01
    “…In conclusion, BP shows promise in natural antitumor biological activity, biological imaging, drug delivery, PTT/PDT/SDT/PAT/PIT, nanovaccines, nanoadjuvants, and combination immunotherapy regimens.…”
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    Design and Fabrication of Ultrathin Metallic Phase Shifters for Visible and Near-Infrared Wavelengths by Qing Guo, Jinkui Chu, Chuanlong Guan, Chuxiao Zhang, Ran Zhang

    Published 2025-01-01
    “…The polarization state of light is critical for biological imaging, acousto-optics, bio-navigation, and many other optical applications. …”
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    Nonlocal Huygens’ meta-lens for high-quality-factor spin-multiplexing imaging by Jin Yao, Yubin Fan, Yunhui Gao, Rong Lin, Zhihui Wang, Mu Ku Chen, Shumin Xiao, Din Ping Tsai

    Published 2025-01-01
    “…Abstract Combining bright-field and edge-enhanced imaging affords an effective avenue for extracting complex morphological information from objects, which is particularly beneficial for biological imaging. Multiplexing meta-lenses present promising candidates for achieving this functionality. …”
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    Deep Transfer Learning for Biology Cross-Domain Image Classification by Chunfeng Guo, Bin Wei, Kun Yu

    Published 2021-01-01
    “…Automatic biology image classification is essential for biodiversity conservation and ecological study. …”
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    Automated cell annotation in multi-cell images using an improved CRF_ID algorithm by Hyun Jee Lee, Jingting Liang, Shivesh Chaudhary, Sihoon Moon, Zikai Yu, Taihong Wu, He Liu, Myung-Kyu Choi, Yun Zhang, Hang Lu

    Published 2025-01-01
    “…Cell identification is an important yet difficult process in data analysis of biological images. Previously, we developed an automated cell identification method called CRF_ID and demonstrated its high performance in Caenorhabditis elegans whole-brain images (Chaudhary et al., 2021). …”
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    Background Information Self-Learning Based Hyperspectral Target Detection by Yufei Tian, Jihai Yang, Shijun Li, Wenning Xu

    Published 2018-01-01
    “…It is especially designed to extract fingerprint and tumor region from hyperspectral biologic images. The experimental results show the validity and the superiority of our method on detecting the biologic information from hyperspectral images.…”
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    Nuclear Morphology Measurements with Angle-Resolved Low Coherence Interferometry For Application To Cell Biology And Early Cancer Detection by Adam Wax, Kevin J. Chalut

    Published 2011-01-01
    “…The study of intact, living cells using non-invasive optical spectroscopic methods offers the opportunity to assess cellular structure and organization in a way that is not possible with commonly used cell biology imaging techniques. We have developed a novel spectroscopic technique for diagnosing disease at the cellular level based on using low-coherence interferometry (LCI) to detect the angular distribution of scattered light. …”
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    Approaching maximum resolution in structured illumination microscopy via accurate noise modeling by Ayush Saurabh, Peter T. Brown, J. Shepard Bryan IV, Zachary R. Fox, Rory Kruithoff, Cristopher Thompson, Comert Kural, Douglas P. Shepherd, Steve Pressé

    Published 2025-01-01
    “…Abstract Biological images captured by microscopes are characterized by heterogeneous signal-to-noise ratios (SNRs) due to spatially varying photon emission across the field of view convoluted with camera noise. …”
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