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Differential geometry-based techniques for characterization of boundary roughness of pulmonary nodules in CT images

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Boundary roughness of a pulmonary nodule is an important indication of its malignancy. The irregularity of the shape of a nodule is represented in terms of a few diagnostic characteristics such as spiculation, lobulation, and sphericity. Quantitative characterization of these diagnostic characteristics is essential for designing a content-based image retrieval system and computer-aided system for diagnosis of lung cancer.

Methods

This paper presents differential geometry-based techniques for computation of spiculation, lobulation, and sphericity using the binary mask of the segmented nodule. These shape features are computed in 3D considering complete nodule.

Results

The performance of the proposed and competing methods is evaluated in terms of the precision, mean similarity, and normalized discounted cumulative gain on 891 nodules of Lung Image Database Consortium and Image Database Resource Initiative. The proposed methods are comparable to or better than gold standard technique. The reproducibility of proposed feature extraction techniques is evaluated using RIDER coffee break data set. The mean and standard deviation of the percent change of spiculation, lobulation, and sphericity are \(1.66\pm 2.36\), \(10.57\pm 11.63\), and \(6.27\pm 7.99\) %, respectively.

Conclusion

The prior works of computation of spiculation, lobulation, and sphericity require a set of four ground truths from radiologists and, hence, can not be used in practice. The proposed methods do not require ground truth information of nodules from radiologists, and hence, it can be used in real-life computer-aided diagnosis system for lung cancer.

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Authors and Affiliations

  1. Department of Electronics and Electrical, Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India

    Ashis Kumar Dhara & Sudipta Mukhopadhyay

  2. Department of Electrical Engineering, Jadavpur University, Kolkata, 700032, India

    Pramit Saha

  3. Department of Radiodiagnosis, Postgraduate Institute of Medical Education and Research, Chandigarh, 160023, India

    Mandeep Garg & Niranjan Khandelwal

Authors
  1. Ashis Kumar Dhara
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  2. Sudipta Mukhopadhyay
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  3. Pramit Saha
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  4. Mandeep Garg
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  5. Niranjan Khandelwal
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Corresponding author

Correspondence to Sudipta Mukhopadhyay.

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Conflicts of interest

This study was funded by Department of Electronics and Information Technology, Govt. of India, Grant Number 1(3)2009-ME&TMD and 1(2) / 2013-ME&TMD/ESDA, respectively. The authors declare that they have no conflict of interest. This work is done using a public lung CT image data set, and for this type of study, formal consent is not required. This article does not contain any studies with human participants or animals performed by any of the authors. Informed consent was obtained from all individual participants included in the study.

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Dhara, A.K., Mukhopadhyay, S., Saha, P. et al. Differential geometry-based techniques for characterization of boundary roughness of pulmonary nodules in CT images. Int J CARS 11, 337–349 (2016). https://doi.org/10.1007/s11548-015-1284-0

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  • DOI: https://doi.org/10.1007/s11548-015-1284-0

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