Projects per year
Sidong Liu is a biomedical informatician and computer scientist, currently based at the Department of Clinical Medicine and Australian Institute of Health Innovation, Macquarie University as a NHMRC Early Career Fellow. He obtained his Bachelor’s degree in Biological Information Technology from Harbin Institute of Technology (HIT), which is a member of the China’s elite C9 League. After graduation from HIT, he further pursued postgraduate study in Bioinformatics and Computer Science in the University of Sydney, and was awarded the Master of Applied Science in Bioinformatics and the Master of Information Technology in Computer Science in 2009 and 2010, respectively. In 2011, he was awarded the highly competitive University of Sydney International Scholarship (USydIS), and started to carry out research on biomedical informatics and artificial intelligence with Professor Weidong Cai and Professor Dagan Feng at School of IT, University of Sydney. In the 4th year of his PhD (2014), he spent one year at the Surgical Planning Laboratory, Brigham and Women's Hospital, Harvard Medical School as a research trainee, and received advanced training in medical image computing under the supervision of Professor Ron Kikinis. After his PhD, he worked at the Brain and Mind Centre and Save Sight Institute, University of Sydney for two years as a postdoctoral research fellow. These experiences positioned him in a clinical environment and enhanced his capability in translational research. Dr Sidong Liu is committed to delivering advanced information technologies to the medical research field, and translating the research outputs into clinical applications.
Computer Science, PhD, University of Sydney
Mar 2011 → Oct 2015
Computer Science, Master of IT, University of Sydney
Feb 2009 → Dec 2009
Bioinformatics, Master of Applied Science, University of Sydney
Feb 2008 → Dec 2008
Bioinformatics, Bachelor, Harbin Institute of Technology
Sep 2003 → Jul 2007
Liu, S., Cui, Z., Liu, W. & Qian, L., Aug 2020. 1 p.
Research output: Contribution to conference › AbstractOpen AccessFile3 Downloads (Pure)
Liu, S., 2020, In : IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13, p. 4738 - 4747 10 p.
Research output: Contribution to journal › ArticleOpen AccessFile1 Downloads (Pure)
Deep learning methodology for differentiating glioma recurrence from radiation necrosis using multimodal magnetic resonance imaging: algorithm development and validationGao, Y., Xiao, X., Han, B., Li, G., Ning, X., Wang, D., Cai, W., Kikinis, R., Berkovsky, S., Di Ieva, A., Zhang, L., Ji, N. & Liu, S., 17 Nov 2020, In : JMIR Medical Informatics. 8, 11, p. 1-15 15 p., e19805.
Research output: Contribution to journal › ArticleOpen AccessFile
Detection of ship targets in photoelectric images based on an improved recurrent attention convolutional neural networkXu, Z., Huo, Y., Liu, K. & Liu, S., Mar 2020, In : International Journal of Distributed Sensor Networks. 16, 3, p. 1-11 11 p.
Research output: Contribution to journal › ArticleOpen AccessFile1 Citation (Scopus)6 Downloads (Pure)
Isocitrate dehydrogenase (IDH) status prediction in histopathology images of gliomas using deep learningLiu, S., Shah, Z., Sav, A., Russo, C., Berkovsky, S., Qian, Y., Coiera, E. & Di Ieva, A., 7 May 2020, In : Scientific Reports. 10, p. 1-11 11 p., 7733.
Research output: Contribution to journal › ArticleOpen AccessFile2 Citations (Scopus)6 Downloads (Pure)
Sidong Liu (Speaker)8 Feb 2019
Activity: Talk or presentation › Invited talk
Sidong Liu (Speaker)Oct 2016
Activity: Talk or presentation › Oral presentation
1 Media contribution