ArticlePloS one2023
Effective and efficient content-based similarity retrieval of large lung CT images based on WSSLN model.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The in-depth combination and application of AI technology and medical imaging, especially high- definition CT imaging technology, make accurate diagnosis and treatment possible. Retrieving similar CT image(CI)s to an input one from the large-scale CI database of labeled diseases is helpful to realize a precise computer-aided diagnosis. In this paper, we take lung CI as an example and propose progressive content-based similarity retrieval(CBSR) method of the lung CIs based on a Weakly Supervised Similarity Learning Network (WSSLN) model. Two enabling techniques (i.e., the WSSLN model and the distance- based pruning scheme) are proposed to facilitate the CBSR processing of the large lung CIs. The main result of our paper is that, our approach is about 45% more effective than the state-of-the-art methods in terms of the mean average precision(mAP). Moreover, for the retrieval efficiency, the WSSLN-based CBSR method is about 150% more efficient than the sequential scan.
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