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Performance evaluation of CAD system for Lung Cancer Detection
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| Author:
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SAJEEV RAM, SHYLAJA, ARUN SAHAYADHAS
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| Abstract:
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Lung Cancer is the foremost cause of eternal rest all around the world. Lung nodules are possible symptom of lung
cancer and the early revealing helps in early treatment and enhance patient’s chances for endurance. An automated
lung nodule segmentation of a region of interest (ROI) is the most challenging problem in clinical practices. For this
basis, CAD systems for lung cancer detection have been intended in many dissertations. This paper reviews some of
the current segmentation algorithms and techniques and also afford a comparative analysis of the accomplishment of
the existing approaches. The LIDC dataset is used for performance analysis of segmentation algorithms. The
experimental analysis shows that watershed algorithm has high accuracy when compared with other algorithms.
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| Keyword:
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Lung Nodules, Otsu Segmentation, Watershed Segmentation, Texture Segmentation, LIDC dataset.
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| EOI:
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-
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| DOI:
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https://doi.org/10.31838/ijpr/2019.11.02.001
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| Download:
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Request For Article
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