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- W4381737483 abstract "Lung cancer is a curable disease if diagnosed early, and early treatment of lung cancer reduces mortality. Early detection of the disease depends on imaging techniques that can be used to detect the disease easily and accurately. An image of the cancer in the affected area is taken from the patient and analyzed using image processing technology. This new Unsupervised Diffusion Classification Algorithm (UDCA) is used to enable the system to easily detect victim crimes. It uses an adaptive median filter algorithm to improve image quality of cancerous areas. Preprocess and segment the image using a supervised image edge detection algorithm. Finally, we use feature extraction to examine the cancer mean, RMS, and regions affected by system performance. UDCA classification method and three main database levels or images can be classified using the proposed method to detect lung cancer enhanced and achieve accurate value in lung cancer diagnosis. Results are obtained through the most standard in-hospital real-time analysis. Hence, this new technique for rapid detection of lung cancer by filter separation method." @default.
- W4381737483 created "2023-06-24" @default.
- W4381737483 creator A5072272288 @default.
- W4381737483 date "2023-04-29" @default.
- W4381737483 modified "2023-09-27" @default.
- W4381737483 title "Multi-Model Detection of Lung Cancer Using Unsupervised Diffusion Classification Algorithm" @default.
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- W4381737483 doi "https://doi.org/10.1109/icdcece57866.2023.10150464" @default.
- W4381737483 hasPublicationYear "2023" @default.
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