(deposit) Lung Tumor Segmentation System on CT Scan Images with Combination of Phase-Based Thresholding Methods

Nurulloh, Insani (2022) (deposit) Lung Tumor Segmentation System on CT Scan Images with Combination of Phase-Based Thresholding Methods. Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.

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Abstract

The speed of information technology also affects the development of digital image processing. In the use of digital image processing, it has been in various fields, one example is in the medical field. In the medical field, an example of using digital image processing is to detect tumors or lung cancer. Lung cancer in Indonesia is ranked 1st in Southeast Asia. In Indonesia alone, the number of people with lung cancer in 2020 was 34,783 new cases. There were 30,843 deaths caused by lung cancer. This study aims to detect and segment lung cancer on CT scan images. Before detecting and segmenting the image on a CT scan, the background and lung fields will be separated by applying the Otsu thresholding method. Nodules or tumor areas in the processed CT scan images will be detected using the Faster R-CNN method and segmented using the Phase-based thresholding method. The results of the detection using the Faster RCNN method get an average confidence level of 0.738838. And the results of segmentation using the phase based thresholding method get an average Precision of 0.9558 or 95%, Sencitivity of 0.7491 or 74%, Specificity of 0.9608 or 96%, Dice Similarity 0.8350 or 83%. Keywords : Lung Tumor, CT Scan, Otsu Thresholding, Faster R-CNN, Phase-Based Thresholding

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