Open AccessDetection of lung Cancer on CT Scan Using Image Processing Techniques
Author(s) -
Osman Mudathir,
Anver Kamil,
Suha Salah,
Marwa Gamar,
Zeinab Nouraldaem
Publication year - 2021
Language(s) - English
Resource type - Journals
ISSN - 1858-7313
DOI - 10.52981/fjes.v10i1.507
Subject(s) - artificial intelligence , computer science , computer vision , feature (linguistics) , stage (stratigraphy) , image processing , pattern recognition (psychology) , segmentation , masking (illustration) , lung cancer , image segmentation , gabor filter , feature extraction , image (mathematics) , cancer detection , image quality , cancer , medicine , pathology , art , paleontology , philosophy , linguistics , visual arts , biology
This paper represents detection of lung cancer using image processing which is followed by image enhancement using three filters. These filters are Gabor, madian and mean filters. Then, image segmentation is applied using a technique called marker controlled watershed with masking that has advantages over other methods in terms of reducing the time needed for detection. On that ground, this method rejoiced with better quality. Finally, an important stage is made to decide whether the lung is infected with cancer or not this stage is called feature extraction .therefore, results were reached with less human efforts.