Filter Based Approach for Automated Detection of Candidate Lung Nodules in 3D Computed Tomography Images
Cancer is considered to be one of the threat causing disease to human health. Amongst the various types of cancers, the one which originates in lung is most fatal. Lung cancer appears in the form of nodules and is caused by anomalous growth of cells in the lung organ. Though detecting and diagnosing lung cancer at the early stages can enhance the survival rate, there are still numerous challenges. Computer Aided Diagnosis (CAD) systems which makes use of various imaging modalities like Computed Tomography (CT) and several image processing techniques, assists the domain experts in the process of prognosis and treatment. A novel technique to detect the candidate lung nodule in 3D CT imagery is presented in this paper which employs minimum area filters and layer based filters designed to eliminate the irregularities, blood vessels and other nodules like lung artifacts. Finally the spherical and spiculated structures are retained by considering the diameter of components under observation. The algorithms are tested against 15 cases each having an average of 250 slices, obtained from LIDC.
KeywordsComputed Tomography Thresholding Lung nodule Computed Aided Diagnosis (CAD)
The authors would like to extend their gratitude to LIDC image database for granting access to the valuable repository of CT scans, which were very helpful in conducting experiments.
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