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. 2013 Mar;9(1):9-17.

Proposed Technique for Accurate Detection/Segmentation of Lung Nodules using Spline Wavelet Techniques

T K Senthil Kumar  1 , E N Ganesh
Affiliations

Proposed Technique for Accurate Detection/Segmentation of Lung Nodules using Spline Wavelet Techniques

T K Senthil Kumar et al. Int J Biomed Sci. 2013 Mar.

Abstract

In this paper we are going to discuss and analyze the different methods which are developed to detect the Lung nodules which cause the lung cancer. At the end of analyzing different methods, the new methodology of detecting the lung nodules using Spline Wavelet technique has been proposed in this paper. Continuous modeling of data often required in medical imaging, Polynomial Splines are especially useful to consider image data as continuum rather than discrete array of pixels. The multi resolution property of Splines makes them prime candidates for constructing wavelet bases. Wavelet tool also let us to compress the original CT image to greater factor without any sacrifice in accuracy of nodule detection. Different Algorithms for segmentation/ detection of lung nodules from CT image is discussed in this paper.

Keywords: lung nodules; medical image segmentation; spline; wavelets.

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Figures

Figure 1
Figure 1
Two step method for lung nodules detection in CT images
Figure 2
Figure 2
a, Original CT Image; b, Enhanced nodules by 3D multi-scale filter; c, 2D Multi-scale filter; d, Takemura’s proposed method
Figure 3
Figure 3
a, Original CT Image; b, Enhanced nodules by 3D multi-scale filter; c, 2D Multi-scale filter; d, Takemura’s proposed method
Figure 4
Figure 4
system architecture
Figure 5
Figure 5
Examples of four different types of cubic splines wavelets and their corresponding duals
See this image and copyright information in PMC

References

    1. Jun WEI, Yoshihiro Hagihara, Akinobu Shimizu, Hidefumi Kobatake. Optimal image feature set for detecting lung nodules on chest X-ray images. CARS 2002 – H.U. Lemke Springer
    1. Classification of Lung nodules in diagnostic CT: an approach on 3D vascular. NHI/NCI Grants Sponsor
    1. Takemura Han, Chen K, Ito Nishikwa, Ito M. Enhancement and detection of lung nodules with Multiscale filters in CT images. International Conference on Intelligent Information, IEEE. 2008
    1. Anitha S, Sridhar S. Segmentation of Lung Lobes and Nodules in CT Images. SIPIJ. 2010;1
    1. Michel Unser. Splines: a perfect fit for medical imaging. SPIE symposium on Medical Imaging. 2002

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