DocumentCode :
738729
Title :
The Validation Index: A New Metric for Validation of Segmentation Algorithms Using Two or More Expert Outlines With Application to Radiotherapy Planning
Author :
Juneja, Prabhjot ; Evans, Philp M. ; Harris, Emma J.
Author_Institution :
Joint Dept. of Phys., R. Marsden NHS Found. Trust, Sutton, UK
Volume :
32
Issue :
8
fYear :
2013
Firstpage :
1481
Lastpage :
1489
Abstract :
Validation is required to ensure automated segmentation algorithms are suitable for radiotherapy target definition. In the absence of true segmentation, algorithmic segmentation is validated against expert outlining of the region of interest. Multiple experts are used to overcome inter-expert variability. Several approaches have been studied in the literature, but the most appropriate approach to combine the information from multiple expert outlines, to give a single metric for validation, is unclear. None consider a metric that can be tailored to case-specific requirements in radiotherapy planning. Validation index (VI), a new validation metric which uses experts´ level of agreement was developed. A control parameter was introduced for the validation of segmentations required for different radiotherapy scenarios: for targets close to organs-at-risk and for difficult to discern targets, where large variation between experts is expected. VI was evaluated using two simulated idealized cases and data from two clinical studies. VI was compared with the commonly used Dice similarity coefficient (DSCpair-wise) and found to be more sensitive than the to the changes in agreement between experts. VI was shown to be adaptable to specific radiotherapy planning scenarios.
Keywords :
biological organs; computerised tomography; image segmentation; medical image processing; radiation therapy; Dice similarity coefficient; automated segmentation algorithms; computed tomography; interexpert variability; multiple expert outlines; organs-at-risk; radiotherapy planning; validation index; Brain; Image segmentation; Indexes; Measurement; Planning; Standards; Tumors; Brain; X-ray imaging and computed tomography; breast; radiotherapy; segmentation; validation; Algorithms; Brain; Humans; Image Processing, Computer-Assisted; Mammography; Radiotherapy Planning, Computer-Assisted; Reproducibility of Results; Tomography, X-Ray Computed;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/TMI.2013.2258031
Filename :
6497630
Link To Document :
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