What is it about?
The primary goal of this effort is to properly identify lung cancer, which is critical in preserving a person's life. This study focuses on the stages involved in detecting lung tumor regions, namely pre-processing, segmentation, and classification models. An adaptive median filter is used in pre-processing to identify the noise. The work's originality seeks to create a simple yet effective model for the rapid identification and U-net architecture based segmentation of lung nodules. This approach focuses on the identification and segmentation of lung cancer by detecting picture normalcy and abnormalities.
Photo by Robina Weermeijer on Unsplash
Why is it important?
The primary goal of this effort is to properly identify lung cancer, which is critical in preserving a person's life.
Read the Original
This page is a summary of: A Hybrid deep learning model for effective segmentation and classification of lung nodules from CT images, Journal of Intelligent & Fuzzy Systems, February 2022, IOS Press, DOI: 10.3233/jifs-212189.
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