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Fissure Extraction Using Dual Tree Complex Wavelet Transform and Lung Lobe Segmentation from CT Lung Images

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Software Engineering Trends and Techniques in Intelligent Systems (CSOC 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 575))

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Abstract

The lungs play a very vital role in human respiratory system. It has five separate lobes which are detached by fissures of three types such as left and right oblique fissure and a horizontal fissure. The way of identifying the fissure lobes in computed tomography scanned lung images are difficult for the medical practitioners because of the incorrect shapes alongside with less contrast and the extraordinary noise associated with it [1]. The last phase of the lung cancer treatment is the elimination of the unhealthy lung by the major surgery. So, it is required to identify the location of the cancer affected part of the lungs by extracting the fissure lobes before making the proposal for the surgery. This paper presents a mechanized process of extracting the left oblique fissures and right oblique fissures by applying the Dual Tree Complex Wavelet Transform from the Computed Tomography lung images. This will help the medical practitioner to identify the lobar fissures from the computed tomography lung images.

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Correspondence to M. Jannathl Firdouse .

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Jannathl Firdouse, M., Balasubramanian, M. (2017). Fissure Extraction Using Dual Tree Complex Wavelet Transform and Lung Lobe Segmentation from CT Lung Images. In: Silhavy, R., Silhavy, P., Prokopova, Z., Senkerik, R., Kominkova Oplatkova, Z. (eds) Software Engineering Trends and Techniques in Intelligent Systems. CSOC 2017. Advances in Intelligent Systems and Computing, vol 575. Springer, Cham. https://doi.org/10.1007/978-3-319-57141-6_9

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  • DOI: https://doi.org/10.1007/978-3-319-57141-6_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57140-9

  • Online ISBN: 978-3-319-57141-6

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