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A GENERAL AND BALANCED REGION-BASED METRIC FOR EVALUATING MEDICAL IMAGE SEGMENTATION ALGORITHMS

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Citation Author(s):
Fabio A M Cappabianco, Pedro F. O. Ribeiro, Paulo A. V. de Miranda, Jayaram K Udupa
Submitted by:
Fabio Augusto C...
Last updated:
19 September 2019 - 9:45am
Document Type:
Poster
Document Year:
2019
Event:
Presenters:
Fabio A M Cappabianco
Paper Code:
3407
 

Evaluating medical imaging segmentation is a very complex problem. Several papers proposed methodologies and differ-
ent metrics pursuing more reliable and unbiased procedures. In this paper, we propose a novel accuracy metric which is more balanced than the well known Dice and Jaccard coefficients. We also prove mathematically that the proposed metric generalizes Dice, Jaccard and the previously proposed Balanced Dice and Balanced Jaccard coefficients. Our experiments show that significant changes in brain tissue segmentation evaluation results are noticed as we applied our new metric.

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