Analysis of Histogram and Grayscale on Chest X-Ray in Lung Cancer Using Image-J

Cancer often attacks the human body, one of which was the lung, and lung cancer was the main cause of death from cancer. Posteranterior (PA) chest radiographic examination is a screening tool for the diagnosis of lung cancer. The computed radiography (CR) modality produces thoracic images quickly and optimally and can be processed as needed, but so far, radiologists have only interpreted images with visual and subjective assessments. So that digital medical image processing is needed by looking at the histogram and gray scale values to increase the quantitative accuracy of lung cancer enforcement, This study aims to analyze the comparison of histograms and grayscale values on CR thoracic images between normal and lung cancer patients. This type of quantitative experimental research was carried out on a sample of 100 chest images consisting of a control group in normal patients and a treatment group in lung cancer patients, totaling 50 images each. Purposive sampling was used for the control group in patients aged 18–60 years and normal, and for the treatment group in patients aged 18–60 years and lung cancer clinicians. All images were calculated in grayscale and displayed as histogram graphics with the Image-J application, and the region of interest (ROI) was performed on the lung lobes at the point of fog or gloom due to pathology, then analyzed statistically using the Independent T-Test. The results show that there is a difference in grayscale values between normal chest images and lung cancer (p 0.001). The grayscale and histogram values in lung cancer chest images (104.780+5.942) are higher and tend to the right compared to the grayscale and histogram values in normal chest images (65.361+3.313).

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Publication Details

Journal
Indonesian Journal of Electronics Electromedical Engineering and Medical Informatics
Published
2025-08-17
DOI
https://doi.org/10.35882/ijeeemi.v5i3.175
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Analysis of Histogram and Grayscale on Chest X-Ray in Lung Cancer Using Image-J

Muchamad Kurniawan, F. Idris, Hernastiti Sedya Utami, Chindi Febriana et al.
Indonesian Journal of Electronics Electromedical Engineering and Medical Informatics
Radiomics and Machine Learning in Medical Imaging
article

Analysis of Histogram and Grayscale on Chest X-Ray in Lung Cancer Using Image-J

Muchamad Kurniawan, F. Idris, Hernastiti Sedya Utami, Chindi Febriana, Fani Susanto, Fannisa Rahma Pradika
article en

Abstract

Cancer often attacks the human body, one of which was the lung, and lung cancer was the main cause of death from cancer. Posteranterior (PA) chest radiographic examination is a screening tool for the diagnosis of lung cancer. The computed radiography (CR) modality produces thoracic images quickly and optimally and can be processed as needed, but so far, radiologists have only interpreted images with visual and subjective assessments. So that digital medical image processing is needed by looking at the histogram and gray scale values to increase the quantitative accuracy of lung cancer enforcement, This study aims to analyze the comparison of histograms and grayscale values on CR thoracic images between normal and lung cancer patients. This type of quantitative experimental research was carried out on a sample of 100 chest images consisting of a control group in normal patients and a treatment group in lung cancer patients, totaling 50 images each. Purposive sampling was used for the control group in patients aged 18–60 years and normal, and for the treatment group in patients aged 18–60 years and lung cancer clinicians. All images were calculated in grayscale and displayed as histogram graphics with the Image-J application, and the region of interest (ROI) was performed on the lung lobes at the point of fog or gloom due to pathology, then analyzed statistically using the Independent T-Test. The results show that there is a difference in grayscale values between normal chest images and lung cancer (p 0.001). The grayscale and histogram values in lung cancer chest images (104.780+5.942) are higher and tend to the right compared to the grayscale and histogram values in normal chest images (65.361+3.313).

Indonesian Journal of Electronics Electromedical Engineering and Medical InformaticsVol. 5(3)
Universitas Muhammadiyah Jember (ID), Muhammadiyah University Purwokerto (ID), Universitas Wijayakusuma Purwokerto (ID)
Openalex Percentile: Top 70%
Radiomics and Machine Learning in Medical Imaging
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