Zobrazeno 1 - 10
of 667
pro vyhledávání: '"Li Yuzhu"'
Current formations commonly rely on invariant hierarchical structures, such as predetermined leaders or enumerated formation shapes. These structures could be unidirectional and sluggish, constraining their adaptability and agility when encountering
Externí odkaz:
http://arxiv.org/abs/2406.11219
Autor:
Huang, Luzhe, Li, Yuzhu, Pillar, Nir, Haran, Tal Keidar, Wallace, William Dean, Ozcan, Aydogan
Histopathological staining of human tissue is essential in the diagnosis of various diseases. The recent advances in virtual tissue staining technologies using AI alleviate some of the costly and tedious steps involved in the traditional histochemica
Externí odkaz:
http://arxiv.org/abs/2404.18458
Autor:
Selcuk, Sahan Yoruc, Yang, Xilin, Bai, Bijie, Zhang, Yijie, Li, Yuzhu, Aydin, Musa, Unal, Aras Firat, Gomatam, Aditya, Guo, Zhen, Angus, Darrow Morgan, Kolodney, Goren, Atlan, Karine, Haran, Tal Keidar, Pillar, Nir, Ozcan, Aydogan
Publikováno v:
BME Frontiers (2024)
Human epidermal growth factor receptor 2 (HER2) is a critical protein in cancer cell growth that signifies the aggressiveness of breast cancer (BC) and helps predict its prognosis. Accurate assessment of immunohistochemically (IHC) stained tissue sli
Externí odkaz:
http://arxiv.org/abs/2404.00837
Autor:
Ma, Guangdong, Yang, Xilin, Bai, Bijie, Li, Jingxi, Li, Yuhang, Gan, Tianyi, Shen, Che-Yung, Zhang, Yijie, Li, Yuzhu, Jarrahi, Mona, Ozcan, Aydogan
Publikováno v:
Laser & Photonics Reviews (2024)
Large-scale and high-dimensional permutation operations are important for various applications in e.g., telecommunications and encryption. Here, we demonstrate the use of all-optical diffractive computing to execute a set of high-dimensional permutat
Externí odkaz:
http://arxiv.org/abs/2402.02397
Autor:
Li, Yuzhu, Pillar, Nir, Li, Jingxi, Liu, Tairan, Wu, Di, Sun, Songyu, Ma, Guangdong, de Haan, Kevin, Huang, Luzhe, Hamidi, Sepehr, Urisman, Anatoly, Haran, Tal Keidar, Wallace, William Dean, Zuckerman, Jonathan E., Ozcan, Aydogan
Publikováno v:
Nature Communications (2024)
Histological examination is a crucial step in an autopsy; however, the traditional histochemical staining of post-mortem samples faces multiple challenges, including the inferior staining quality due to autolysis caused by delayed fixation of cadaver
Externí odkaz:
http://arxiv.org/abs/2308.00920
Publikováno v:
Light: Science & Applications (2023)
Histological staining is the gold standard for tissue examination in clinical pathology and life-science research, which visualizes the tissue and cellular structures using chromatic dyes or fluorescence labels to aid the microscopic assessment of ti
Externí odkaz:
http://arxiv.org/abs/2211.06822
This paper proposes an adaptive tracking strategy with mass-inertia estimation for aerial transportation problems of multi-rotor UAVs. The dynamic model of multi-rotor UAVs with disturbances is firstly developed with a linearly parameterized form. Su
Externí odkaz:
http://arxiv.org/abs/2209.08209
Autor:
Yang, Xilin, Bai, Bijie, Zhang, Yijie, Li, Yuzhu, de Haan, Kevin, Liu, Tairan, Ozcan, Aydogan
Publikováno v:
ACS Photonics (2022)
Pathological diagnosis relies on the visual inspection of histologically stained thin tissue specimens, where different types of stains are applied to bring contrast to and highlight various desired histological features. However, the destructive his
Externí odkaz:
http://arxiv.org/abs/2207.06578
Virtual staining of defocused autofluorescence images of unlabeled tissue using deep neural networks
Autor:
Zhang, Yijie, Huang, Luzhe, Liu, Tairan, Cheng, Keyi, de Haan, Kevin, Li, Yuzhu, Bai, Bijie, Ozcan, Aydogan
Publikováno v:
Intelligent Computing (2022)
Deep learning-based virtual staining was developed to introduce image contrast to label-free tissue sections, digitally matching the histological staining, which is time-consuming, labor-intensive, and destructive to tissue. Standard virtual staining
Externí odkaz:
http://arxiv.org/abs/2207.02946
Autor:
Liu, Tairan, Li, Yuzhu, Koydemir, Hatice Ceylan, Zhang, Yijie, Yang, Ethan, Eryilmaz, Merve, Wang, Hongda, Li, Jingxi, Bai, Bijie, Ma, Guangdong, Ozcan, Aydogan
Publikováno v:
Nature Biomedical Engineering (2023)
We present a rapid and stain-free quantitative viral plaque assay using lensfree holographic imaging and deep learning. This cost-effective, compact, and automated device significantly reduces the incubation time needed for traditional plaque assays
Externí odkaz:
http://arxiv.org/abs/2207.00089