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Output details

11 - Computer Science and Informatics

University College London

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Output 34 of 261 in the submission
Article title

Automatic Segmentation and Quantitative Analysis of the Articular Cartilages From Magnetic Resonance Images of the Knee

Type
D - Journal article
Title of journal
IEEE Trans Med Imaging
Article number
-
Volume number
29
Issue number
1
First page of article
55
ISSN of journal
0278-0062
Year of publication
2010
URL
-
Number of additional authors
3
Additional information

<23>Originality: introduces a fully automatic scheme to segment MR image of the human knee. The framework is the first to date to provide a fully automatic segmentation of the entire structure (3 cartilages, 3 bones).

Significance: a novel multi-component statistical shape model is presented, combined with deformable model and local Bayesian classification to provide extra refinement of the segmentation. The framework has been patented world-wide and been licensed to Siemens..

Rigour: the technique was tested against other existing techniques and proved to be the most accurate and robust. The testing was done using a large dataset of manually segmented knees.

Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
25
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-