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Homepage of Yihui Huang(English, 中文) |
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| Ph.D. candidate | ||||
| Department of Electronic Science,School of Electronic Science and Engineering (National Model Microelectronics College), Xiamen University. | ||||
| Email: hyh261@163.com | ||||
| Computational Sensing Group at Xiamen University | ||||
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Biosketch |
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Yihui Huang is a PhD candidate of Department of Electronic Science at Xiamen University in China.
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Fast magnetic resonance imaging |
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Machine learning and deep learning | |||||||
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Medical image processing and analysis |
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Ph.D. candidate (Sept. 2018-Current) Advisor: Xiaobo Qu Major : Electronics and Communication Engineering. Xiamen University, Fujian Province, China. |
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Graduate Student (Sept. 2015-June 2018) Advisor: Prof. Qianjin Feng Major : Department of Biomedical Engineering, Southern Medical University, Guangdong Province, China. |
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B.S. (Sept. 2011-June 2015) Department of Biomedical Engineering, |
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| Research and Teaching Experiences | ||||||||||
| (a)Medical image processing and analysis | ||||||||||
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Develop effective texture features of dynamic contrast enhanced-MRI(DCE-MRI) for classifying breast cancer. |
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Develop the algorithm of multi-region brain glioma segmentation based on MRI. |
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Attending the 3rd Medical Imaging Computing Seminar(MICS’16, July 15-17, 2016, Guangzhou). |
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Attending Chinese Biomedical Engineering Conference(April 20-22, 2017, Beijing). |
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Attending the 4th Medical Imaging Computing Seminar (MICS’17, July 15-16, 2017, Shanghai). |
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Attending 4th International Medical Imaging Symposium in Suzhou(November 4-6, 2017, Suzhou). |
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| (b)NMR spectrum reconstruction | ||||||||||
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Develop a deep learning method, called DLNMR, for fast, high quality and reliable NMR spectrum reconstruction under the condition of limited experimental spectra. |
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Develop software interface for the DLNMR technology transference to company. |
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| (c) Teaching experience | ||||||||||
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Teaching assistant (2016’s spring semester) |
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Teaching assistant (2019’s fall semester) |
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| Selected Wards | ||||||||||
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2010, The third prize in Fujian Division, Chinese Chemistry Olympiad |
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| Professional Skills | ||||||||||
| (a) Magnetic resonance instruments | ||||||||||
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Basic operating skills of human magnetic resonance imaging scanner (GE, MR750w 3.0T) | |||||||||
| (b) Deep learning | ||||||||||
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Deep learning framework: tensorflow, keras. |
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Mastered programming languages: C/C++, Java, Python and Matlab. |
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Participate in the building of Linux and Windows deep learning server platform. |
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| (a) Journal paper | ||||||||||
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Yihui Huang, Qianjin Feng*. Segmentation of brain tumor on magnetic resonance images using 3D full-convolutional densely connected convolutional networks. Journal of Southern Medical University, 2018, 38(6): 661-668. (in Chinese) |
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Xiaobo Qu*, Yihui Huang, Hengfa Lu, Tianyu Qiu, Di Guo, Tatiana Agback, Vladislav Orekhov, Zhong Chen*, Accelerated Nuclear Magnetic Resonance Spectroscopy with Deep Learning, Angewandte Chemie International Edition,DOI:10.1002/anie.201908162,2019. (SCI, JCR 1, TOP Journal, IF 12.26) | |||||||||
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Yonggui Yang,Xiaobo Qu , Yihui Huang,Khan Afsar, Gen Yan, Gang Guo* and Shaoyin Duan*. Preliminary application of 3.0 T magnetic resonance chemical exchange saturation transfer imaging in brain metastasis of lung cancer., BMC Medical Imaging,20, 4 (2020).DOI: 10.1186/s12880-019-0400-y | |||||||||
| (b)Conference abstracts | ||||||||||
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Xiaobo Qu*,Yihui Huang,Hengfa Lu, Tianyu Qiu, Di Guo, Tatiana Agback, Vladislav Orekhov,and Zhong Chen. Deep learning-based fast magnetic resonance spectroscopy, International Society for Magnetic Resonance in Medicine 28th Scientific Meeting-ISMRM’20, Sydney, Australia, April 18-23, 2020, pp. 4182. | |||||||||
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Tieyuan Lu, Xinlin Zhang,Yihui Huang,Di Guo, and Xiaobo Qu*.pISTA-SENSE-ResNet for parallel MRI reconstruction, International Society for Magnetic Resonance in Medicine 28th Scientific Meeting-ISMRM’20, Sydney, Australia, April 18-23, 2020, pp.4398. | |||||||||
| (c)preprint | ||||||||||
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Tieyuan Lu, Xinlin Zhang,Yihui Huang,Di Guo, and Xiaobo Qu*.pISTA-SENSE-ResNet for parallel MRI reconstruction, arXiv:1910.00650, 2019. | |||||||||