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A parameterized logarithmic image processing method with Laplacian of Gaussian filtering for lung nodule enhancement in chest radiographs

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Abstract

The enhancement of lung nodules in chest radiographs (CXRs) plays an important role in the manual as well as computer-aided detection (CADe) lung cancer. In this paper, we proposed a parameterized logarithmic image processing (PLIP) method combined with the Laplacian of a Gaussian (LoG) filter to enhance lung nodules in CXRs. We first applied several LoG filters with varying parameters to an original CXR to enhance the nodule-like structures as well as the edges in the image. We then applied the PLIP model, which can enhance lung nodule images with high contrast and was beneficial in extracting effective features for nodule detection in the CADe scheme. Our method combined the advantages of both the PLIP algorithm and the LoG algorithm, which can enhance lung nodules in chest radiographs with high contrast. To test our nodule enhancement method, we tested a CADe scheme, with a relatively high performance in nodule detection, using a publically available database containing 140 nodules in 140 CXRs enhanced through our nodule enhancement method. The CADe scheme attained a sensitivity of 81 and 70 % with an average of 5.0 frame rate (FP) and 2.0 FP, respectively, in a leave-one-out cross-validation test. By contrast, the CADe scheme based on the original image recorded a sensitivity of 77 and 63 % at 5.0 FP and 2.0 FP, respectively. We introduced the measurement of enhancement by entropy evaluation to objectively assess our method. Experimental results show that the proposed method obtains an effective enhancement of lung nodules in CXRs for both radiologists and CADe schemes.

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Acknowledgments

This work was supported in part by the National Science Foundation of China (NSFC) 81101116, Jiangsu Province Key Technology R&D Program BE2012630, and the Foundation of Hujiang (C14002). The authors declare that they have no conflict of interest. The database ‘A’ is approved by the ethic committee at Xinhua Hospital (Reference number 20130021). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.

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Authors and Affiliations

  1. School of Optical Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China

    Sheng Chen & Bao Chen

  2. Xinhua Hospital, School of Biomedical Engineering, Shanghai Jiaotong University, Shanghai, China

    Liping Yao

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  1. Sheng Chen
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  2. Liping Yao
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  3. Bao Chen
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Correspondence to Sheng Chen or Liping Yao.

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Chen, S., Yao, L. & Chen, B. A parameterized logarithmic image processing method with Laplacian of Gaussian filtering for lung nodule enhancement in chest radiographs. Med Biol Eng Comput 54, 1793–1806 (2016). https://doi.org/10.1007/s11517-016-1469-x

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  • DOI: https://doi.org/10.1007/s11517-016-1469-x

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