Generative Localization With Uncertainty Estimation Through Video-CT Data for Bronchoscopic Biopsy
- Submitting institution
-
The University of Sheffield
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 5242
- Type
- D - Journal article
- DOI
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10.1109/LRA.2019.2955941
- Title of journal
- IEEE Robotics and Automation Letters
- Article number
- -
- First page
- 258
- Volume
- 5
- Issue
- 1
- ISSN
- 2377-3766
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2019
- 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
- No
- Number of additional authors
-
3
- Research group(s)
-
J - Visual Computing
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Lung cancer is the most common cause of cancer death worldwide. Early diagnosis has the potential to save millions of lives. This paper presents a visually-guided localisation system for use in early-stage lung cancer diagnosis and treatment and is the first research to use probabilistic machine learning to estimate the camera localisation with uncertainties. This research was part of the EPSRC REBOT project led by Prof Guangzhong Yang (Fellow of Royal Academy of Engineering), involving a collaboration between the world-leading Hamlyn Centre for Robotic Surgery (Imperial College London) and Oxford Robotics Institute (University of Oxford).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -