An Efficient AGMM-Based Framework for Lung Cancer Segmentation and Severity

Abstract

 

Lung cancer develops due to the uncontrolled growth of abnormal cells in the lungs and poses a significant health risk, as the lungs contain extensive blood vessels and lymphatic pathways that facilitate metastasis. Early identification and staging of lung tumors are crucial factors in improving patient survival rates. Computed tomography (CT) imaging is widely used for detecting lung abnormalities, as it provides detailed information about lung structures. Accurate medical image segmentation plays a vital role in enhancing the detection of lesion regions.