The essential organ for respiration and inspiration of human beings are Lungs. It consists of five distinct lobes which are separated by three fissures (the boundaries of lung lobes are the areas containing fissures and having absence of bronchial trees). They are two oblique (left and right) fissures and one horizontal fissure. The left lung consist of left oblique fissure which separates the superior and middle lobes. The right lung consist of right oblique fissure which separates superior and middle lobes and right horizontal fissure which separates middle and inferior lobes. The identification of the lobar fissures in isotropic Computed Tomography (CT) images are very difficult even for the experienced surgeons because of its variable shape and appearance along with low contrast and high noise association with it. Further the fissure thickness is observed to be around 2 pixels (approximately 1.2mm) complicates the fissure identification. The identification of lobar fissure in CT images will be helpful for the surgeon to identify the cancer location before they plan for surgery. The surgical removal of the diseased lung is the final stage for treating the lung cancer. Therefore it is necessary to find the cancer location at the early stage to treat it. This paper presents an automated method to extract the left and right oblique fissures from the CT lung images. The proposed method is implemented in two phases. In the first phase, the fissure region is located. In the second phase, the found lobar fissures are extracted. The obtained results show that the proposed work can help the surgeon to identify the cancer location.
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[v1] 2012-08-18 12:55:38
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