A hybrid patient-specific biomechanical model based image registration method for the motion estimation of lungs
- Submitting institution
-
Loughborough University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1962
- Type
- D - Journal article
- DOI
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10.1016/j.media.2017.04.003
- Title of journal
- Medical Image Analysis
- Article number
- C
- First page
- 87
- Volume
- 39
- Issue
- -
- ISSN
- 1361-8415
- Open access status
- Deposit exception
- Month of publication
- April
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
5
- Research group(s)
-
-
- Citation count
- 13
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work has impacted the state of the art by, employing a new solution for lung respiration motion prediction. The proposed methods have been used as one of the state-of-the-art algorithms used for comparison by other international research groups (e.g. University of Washington, Medical Physics, 45(2), 2017 and Nanjing University of Science and Technology, IEEE Access, 6, 2018)
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -