Skip to menu Skip to content Skip to footer
The University of Queensland
  • Study
  • Research
  • Partners and community
  • About
School of Information Technology and Electrical Engineering
  • Home
  • About
    • About
    • News
    • Events
    • Our people
    • Facilities
    • Occupational health and safety
    • Engineering and Technical Support Group
  • Study
  • Research
    • Research
    • Research Centres
    • UQ Election Ad Data Dashboard
  • Current students
    • Current students
    • Academic advice
    • Guidelines and policies for students
    • Postgraduate research students
    • Student Consultative Committee
    • Thesis coursework information
    • ITEE Learning Centre tutors
  • Engage
    • Engage
    • Community workshops and events
    • Industry Advisory Board
    • Partner with us
  • Giving
  • Contact
  • Study
  • Research
  • Partners and community
  • About
  • UQ home
  • News
  • Events
  • Give
  • Contact
  • UQ home
  • News
  • Events
  • Give
  • Contact
School of Information Technology and Electrical Engineering
  • Home
  • About
    • News
    • Events
    • Our people
    • Facilities
    • Occupational health and safety
    • Engineering and Technical Support Group
  • Study
  • Research
    • Research Centres
    • UQ Election Ad Data Dashboard
  • Current students
    • Academic advice
    • Guidelines and policies for students
    • Postgraduate research students
    • Student Consultative Committee
    • Thesis coursework information
    • ITEE Learning Centre tutors
  • Engage
    • Community workshops and events
    • Industry Advisory Board
    • Partner with us
  • Giving
  • Contact

Dr Shanshan Shan

s.shan@uq.edu.au

Publications

Journal Articles (3)

Journal Articles

Shan, Shanshan, Li, Mao, Li, Mingyan, Tang, Fangfang, Crozier, Stuart and Liu, Feng (2021). ReUINet: A fast GNL distortion correction approach on a 1.0 T MRI-Linac scanner. Medical Physics, 48 (6), 2991-3002. doi: 10.1002/mp.14861
Li, Mao, Shan, Shanshan, Chandra, Shekhar S., Liu, Feng and Crozier, Stuart (2020). Fast geometric distortion correction using a deep neural network: implementation for the 1 Tesla MRI-Linac system. Medical Physics, 47 (9) mp.14382, 4303-4315. doi: 10.1002/mp.14382
Shan, Shanshan, Li, Mingyan, Tang, Fangfang, Ma, Huan, Liu, Feng and Crozier, Stuart (2019). Gradient Field Deviation (GFD) correction using a hybrid-norm approach with wavelet sub-band dependent regularisation: implementation for radial MRI at 9.4 T. IEEE Transactions on Biomedical Engineering, 66 (9), 1-1. doi: 10.1109/TBME.2019.2895091
Australian Aboriginal Flag Torres Strait Islander Flag UQ acknowledges the Traditional Owners and their custodianship of the lands on which UQ is situated. — Reconciliation at UQ
  • Media

    • Media team contacts
    • Find a subject matter expert
    • UQ news
  • Working at UQ

    • Current staff
    • Careers at UQ
    • Strategic plan
    • Staff support
    • IT support for staff
  • Current students

    • my.UQ
    • Programs and courses
    • Key dates
    • Student support
    • IT support for students
  • Library

    • Library
    • Locations and hours
    • Library services
    • Research tools
  • Contact

    • Contact UQ
    • Find a researcher
    • Faculties, schools, institutes and centres
    • Divisions and departments
    • Campuses, maps and transport
    • Media team contacts
    • Find a subject matter expert
    • UQ news
    • Current staff
    • Careers at UQ
    • Strategic plan
    • Staff support
    • IT support for staff
    • my.UQ
    • Programs and courses
    • Key dates
    • Student support
    • IT support for students
    • Library
    • Locations and hours
    • Library services
    • Research tools
    • Contact UQ
    • Find a researcher
    • Faculties, schools, institutes and centres
    • Divisions and departments
    • Campuses, maps and transport
Web login
  • © The University of Queensland
  • ABN: 63 942 912 684
  • CRICOS: 00025B
  • TEQSA: PRV12080
  • Privacy and terms of use
  • Accessibility
  • Right to information
  • Feedback