Now a day’s Lung Cancer providing to be a catastrophic Threat to the Mankind and is main cause of Human deaths among other cancer related casualties. Early detection of lung cancer is the most challenging problem in medical research. This is due to abnormal formation of cells which may be sometime overlap. The presence of solitary pulmonary nodules in human lungs are in the form of malignant determines the gravity of lung ailments. Image processing which is growing research area has been playing a central role in the detection of lung cancer images. Among many imaging modalities CT leads to higher resolution. In this project an automatic lung nodule detection system is proposed. Many segmentation methods have been used to detect the malignant cells in lung affected CT images. The edges of segmented object are not clearly identified using conventional segmentation methods. Hence the detection and extraction of lung tumor is not accurate. The proposed system is fractional calculus based segmentation through which the segmentation and edge detection process become adequate to extract lung tumor in CT images.
Article Details
Unique Paper ID: 144718
Publication Volume & Issue: Volume 4, Issue 2
Page(s): 248 - 257
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National Conference on Sustainable Engineering and Management - 2024