11 March 2014 Complementary cumulative precision distribution: a new graphical metric for medical image retrieval system
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Abstract
Several single valued measures have been proposed by researchers for the quantitative performance evaluation of medical image retrieval systems. Precision and recall are the most common evaluation measures used by researchers. Amongst graphical measures proposed, precision vs. recall graph is the most common evaluation measure. Precision vs. recall graph evaluates di®erent systems by varying the operating points (number of top retrieval considered). However, in real life the operating point for di®erent applications are known. Therefore, it is essential to evaluate di®erent retrieval systems at a particular operating point set by the user. None of the graphical metric provides the variation of performance of query images over the entire database at a particular operating point. This paper proposes a graphical metric called Complementary Cumulative Precision Distribution (CCPD) that evaluates di®erent systems at a particular operating point considering each images in the database for query. The strength of the metric is its ability to represent all these measures pictorially. The proposed metric (CCPD) pictorially represents the di®erent possible values of precision and the fraction of query images at those precision values considering number of top retrievals constant. Di®erent scalar measures are derived from the proposed graphical metric (CCPD) for e®ective evaluation of retrieval systems. It is also observed that the proposed metric can be used as a tie breaker when the performance of di®erent methods are very close to each other in terms of average precision.
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Jatindra Kumar Dash, Jatindra Kumar Dash, Sudipta Mukhopadhyay, Sudipta Mukhopadhyay, Niranjan Khandelwal, Niranjan Khandelwal, } "Complementary cumulative precision distribution: a new graphical metric for medical image retrieval system", Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, 90371S (11 March 2014); doi: 10.1117/12.2043156; https://doi.org/10.1117/12.2043156
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