Robust and Accurate Shape Model Matching Using Random Forest Regression-Voting

Claudia Lindner; Paul A Bromiley; Mircea C Ionita; Timothy F Cootes

doi:10.1109/TPAMI.2014.2382106

Robust and Accurate Shape Model Matching Using Random Forest Regression-Voting

Claudia Lindner, Paul A Bromiley, Mircea C Ionita, Timothy F Cootes

Division of Informatics, Imaging & Data Sciences (L5)

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	1862-1874
Number of pages	13
Journal	IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume	37
Issue number	9
DOIs	https://doi.org/10.1109/TPAMI.2014.2382106
Publication status	Published - 18 Dec 2014

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10.1109/TPAMI.2014.2382106

http://doi.ieeecomputersociety.org/10.1109/TPAMI.2014.2382106

ASPIRE™: Using Machine Learning to detect undiagnosed fractures in patients with osteoporosis
Bromiley, P. (Participant), Cootes, T. (Participant), Kariki, E. (Participant) & Adams, J. (Participant)
Impact: Technological impacts, Health and wellbeing
Bonefinder: Development of a fully automatic software tool for bone shape analyses from medical images to improve accuracy and aid clinical decisions in the diagnosis and monitoring of various medical conditions
Lindner, C. (Corresponding participant), Cootes, T. (Participant) & Wallis, G. (Collaborator)
Impact: Health and wellbeing, Economic

Cite this

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title = "Robust and Accurate Shape Model Matching Using Random Forest Regression-Voting",

author = "Claudia Lindner and Bromiley, \{Paul A\} and Ionita, \{Mircea C\} and Cootes, \{Timothy F\}",

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T1 - Robust and Accurate Shape Model Matching Using Random Forest Regression-Voting

AU - Lindner, Claudia

AU - Bromiley, Paul A

AU - Ionita, Mircea C

AU - Cootes, Timothy F

PY - 2014/12/18

Y1 - 2014/12/18

U2 - 10.1109/TPAMI.2014.2382106

DO - 10.1109/TPAMI.2014.2382106

M3 - Article

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EP - 1874

JO - IEEE Transactions on Pattern Analysis and Machine Intelligence

JF - IEEE Transactions on Pattern Analysis and Machine Intelligence

IS - 9

ER -

Robust and Accurate Shape Model Matching Using Random Forest Regression-Voting

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Impacts

ASPIRE™: Using Machine Learning to detect undiagnosed fractures in patients with osteoporosis

Bonefinder: Development of a fully automatic software tool for bone shape analyses from medical images to improve accuracy and aid clinical decisions in the diagnosis and monitoring of various medical conditions

Cite this