Zobrazeno 1 - 10
of 92
pro vyhledávání: '"Ye, Jiarong"'
Deep learning based medical image recognition systems often require a substantial amount of training data with expert annotations, which can be expensive and time-consuming to obtain. Recently, synthetic augmentation techniques have been proposed to
Externí odkaz:
http://arxiv.org/abs/2308.04020
Autor:
Ye, Jiarong, Yeh, Yin-Ting, Xue, Yuan, Wang, Ziyang, Zhang, Na, Liu, He, Zhang, Kunyan, Ricker, RyeAnne, Yu, Zhuohang, Roder, Allison, Lopez, Nestor Perea, Organtini, Lindsey, Greene, Wallace, Hafenstein, Susan, Lu, Huaguang, Ghedin, Elodie, Terrones, Mauricio, Huang, Shengxi, Huang, Sharon Xiaolei
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America (2022)
Rapid identification of newly emerging or circulating viruses is an important first step toward managing the public health response to potential outbreaks. A portable virus capture device coupled with label-free Raman Spectroscopy holds the promise o
Externí odkaz:
http://arxiv.org/abs/2206.02788
Publikováno v:
In Biomedicine & Pharmacotherapy October 2024 179
Autor:
Xue, Yuan, Ye, Jiarong, Zhou, Qianying, Long, Rodney, Antani, Sameer, Xue, Zhiyun, Cornwell, Carl, Zaino, Richard, Cheng, Keith, Huang, Xiaolei
Publikováno v:
Medical Image Analysis 67 (2021): 101816
Histopathological analysis is the present gold standard for precancerous lesion diagnosis. The goal of automated histopathological classification from digital images requires supervised training, which requires a large number of expert annotations th
Externí odkaz:
http://arxiv.org/abs/2111.06399
Generative models have been applied in the medical imaging domain for various image recognition and synthesis tasks. However, a more controllable and interpretable image synthesis model is still lacking yet necessary for important applications such a
Externí odkaz:
http://arxiv.org/abs/2111.06398
Autor:
Ye, Jiarong, Xue, Yuan, Long, L. Rodney, Antani, Sameer, Xue, Zhiyun, Cheng, Keith, Huang, Xiaolei
Synthesizing realistic medical images provides a feasible solution to the shortage of training data in deep learning based medical image recognition systems. However, the quality control of synthetic images for data augmentation purposes is under-inv
Externí odkaz:
http://arxiv.org/abs/2008.11331
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Akademický článek
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Supervised training of an automated medical image analysis system often requires a large amount of expert annotations that are hard to collect. Moreover, the proportions of data available across different classes may be highly imbalanced for rare dis
Externí odkaz:
http://arxiv.org/abs/1912.03837
Autor:
Xue, Yuan, Zhou, Qianying, Ye, Jiarong, Long, L. Rodney, Antani, Sameer, Cornwell, Carl, Xue, Zhiyun, Huang, Xiaolei
Cervical intraepithelial neoplasia (CIN) grade of histopathology images is a crucial indicator in cervical biopsy results. Accurate CIN grading of epithelium regions helps pathologists with precancerous lesion diagnosis and treatment planning. Althou
Externí odkaz:
http://arxiv.org/abs/1907.10655