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CAD System forLung cancer detection using Adaptive NeuroFuzzy Classifier
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| Author:
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C.S.SHYLAJA , R.ANANDAN, A.SAJEEV RAM
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| Abstract:
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This paper presents a computer aided diagnosissystem to recognize lung cancer at its earlier stage and in this
research article a new approach is presented. In several research studies CAD system for lung cancer is
implemented. An effective lung cancer detection CAD system generally comprises several steps which
includes: Image preprocessing to enhance the image, Segmenting the image to find the lesion present in an
image, Features are to be extracted to train the system and Classification to be done whether the image is
having lesions or not. The proposed CAD system combines image processing and artificial neuro fuzzy
classifier and produces accuracy of 98.1% for cancerous nodules.
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| Keyword:
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Computed Tomography, Fast local laplacian filter, adaptive thresholding, Adaptive NeuroFuzzy Classifier,Feature Extraction.
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| EOI:
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| DOI:
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https://doi.org/10.31838/ijpr/2019.11.04.044
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| Download:
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Request For Article
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