Image Retrieval Algorithm of Pulmonary Nodules Based on Similarity Measurement

doi:10.12068/j.issn.1005-3026.2018.09.003

Journal of Northeastern University Natural Science ›› 2018, Vol. 39 ›› Issue (9): 1226-1231.DOI: 10.12068/j.issn.1005-3026.2018.09.003

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Image Retrieval Algorithm of Pulmonary Nodules Based on Similarity Measurement

WEI Guo-hui^1,2， QI Shou-liang¹， QIAN Wei¹， ZHANG Kui-xing ²

1. School of Sino-Dutch Biomedical & Information Engineering， Northeastern University， Shenyang 110169， China; 2. School of Science and Engineering， Shandong University of Traditional Chinese Medicine， Jinan 250355， China.

Received:2017-05-08 Revised:2017-05-08 Online:2018-09-15 Published:2018-09-12
Contact: QI Shou-liang
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Abstract

Abstract: In order to overcome the shortcomings that CT of pulmonary lesions is complex and is very easy to lead to misdiagnosis， a medical image retrieval algorithm based on similarity measurement was proposed to diagnose lung cancer. The similarity measurement maintains the semantic relevance and visual similarity of the image. Firstly， a distance metric learning algorithm was constructed to learn a Mahalanobis distance on the basis of the proposed similarity measurement. Secondly， a novel medical image retrieval algorithm was proposed based on the learned distance metric to diagnose lung cancer. The study results demonstrate the feasibility and effectiveness of the proposed retrieval algorithm in lung cancer diagnosis.

Key words: medical image retrieval, lung cancer, similarity measurement, distance metric learning, texture features

CLC Number:

TP391.41

WEI Guo-hui， QI Shou-liang， QIAN Wei， ZHANG Kui-xing. Image Retrieval Algorithm of Pulmonary Nodules Based on Similarity Measurement[J]. Journal of Northeastern University Natural Science, 2018, 39(9): 1226-1231.

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Image Retrieval Algorithm of Pulmonary Nodules Based on Similarity Measurement

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