Improvements to conventional methods for determining lung cancer areas from CT scan images using ImageJ - software

Edwar Iswardy, Munzir Munzir, Evi Yufita

Abstract

Early detection of lung cancer will definitely help the patients in treating the illness precisely and as early as possible.  One of the methods used to detect lung cancer is through CT scan examination. The images from CT scan will show the cancer area of lung describing the severity of lungs affected by cancer. However, the conventional method is often not accurate. Therefore, this research  aims to determine the area of cancer by segmenting the lung organs affected by cancer using Image-J software. The edge detection method was employed to segment an image. The results show that by using the proposed method, the largest cancer area is obtained in the seventh slice with the area of 15.39 cm2 and the smallest cancer area is obtained  in  the  first  slice  with  the  area  of 1.52  cm2. Whereas by using the convetional method, the  largest  cancer  area  is obtained in the fourth slice with the area of 20.57 cm2  and the smallest cancer area is  obtained  in  the  teenth  slice  with  the  area  of 3.52  cm2. The area of lung cancer in each CT Scan slice determined using ImageJ software is more accurate than the conventional method. For that reason, the  proposed  technique  is potential to improve the accuracy of a medical image analysis.

Keywords

lung cancer; CT scan image; edge detection; segmentation; image-J

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References

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