Multi-Model Detection of Lung Cancer Using Unsupervised Diffusion Classification Algorithm

• Published in: 2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) pp. 1 - 5
• Main Author: Bhardwaj, Rishabh
• Format: Conference Proceeding
• Language: English
• Published: IEEE 29.04.2023
• Subjects: Diagnose Lung Cancer; Filtering algorithms; Future extraction; Lung; Lung cancer; Preprocessing; Real-time systems; Segmentation; Sensitivity; Surveys; System performance; UDCA Algorithm
• DOI: 10.1109/ICDCECE57866.2023.10150464

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.