Abstract—Lung cancer is the most common type of cancer
among males worldwide. It accounts for one of every five cancerrelated
fatalities and is prevalent in people aged 55 to 65.
Detecting lung cancer in its earliest stages is a crucial step in
the treatment process that can significantly increase the chance
of survival. In this paper, we used image processing techniques
with MATLAB on computed tomography (CT) images of lung
cancer for multiple patients to determine the location and extent
of cancerous spots. The stages included image analysis and
segmentation, feature extraction, and candidate identification as
distinct regions of interest (ROI). Algorithms based on machine
learning were utilized to classify cancer from the ROIs of
candidates by extracting the characteristics required for the
classification of pathologic features from the annotated ROIs.
Comparing the evaluated algorithms in order to identify the
optimal algorithm for cancer detection.

Conference Title

2023 10th International Conference on Electrical and Electronics Engineering (ICEEE), pp. 24-30, doi: 10.1109/ICEEE59925.2023.00012

Conference Country

Turkey

Conference Date

May 8, 2023 - May 10, 2023

Conference Sponsor

IEEE

Additional Info

Conference Website