Identification of Pulmonary Nodules Using Fuzzy Connectivity Map Construction from the Choice of an Ideal Seed

• Tiago Emmanuel Praxedes Silva UFAL
• Marcelo Costa Oliveira UFAL

Abstract

The main objective of this study was to compare quantitatively the accuracy of the segmentation through the algorithm for map construction of fuzzy connectedness based on the choice of an ideal seed compared to manual segmentation. We randomly selected 30 nodules of the project "Lung Image Database Consortium". The developed algorithm was effective in identifying lung nodules reaching 90.4% accuracy. Moreover, it surpassed the accuracy of the traditional segmentation algorithm for region growing at 9.1%. Therefore, this technique has the potential to be used as a tool for the aid to diagnosis of lung cancer.

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