eng Oriental Scientific Publishing Company Biomedical and Pharmacology Journal 0974-6242 2025-02-20 18 March Spl Edition 121 138 10.13005/bpj/3077 63742 article Asaad Babker 1 Rania Saad Suliman 2 Aisha Ali M Ghazwani 2 Wiam AlHarbi 3 Vyacheslav Lyashenko 4 Department of Medical Laboratory Sciences, College of Health Sciences, Gulf Medical University, Ajman, UAE. Department of Clinical Laboratory Sciences, Prince Sultan Military College for Health Sciences, Dhahran, Saudi Arabia Histopathology Department, King Fahad Military Medical Complex, Dhahran, Saudi Arabia. Department of Media Systems and Technology, Kharkiv National University of Radio Electronics, Kharkiv, Ukraine Digital medical images study, analysis and processing is one of medical visualization areas, which helps to improve diagnostic diseases and detection, monitoring their progression and treatment. In this regard, the analysis of cytological images is important and effective, it allows to study various cellular structures. One of the components of such research is the allocation of potential areas of interest, considering the specifics of color medical images presentation. The paper proposes a new combined approach for identifying potential areas of interest based on edge detection operators, which is compared with the corresponding classical methods. It is shown that the proposed combined approach gives results no worse than classical methods, and for some types of images, even better. At the same time, resulting images quality assessments compactness is achieved, the range of the obtained results for making effective decisions is expanded depending on the specification of the analysis goals. It is shown that for images with a semi-transparent background, low-contrast difference between the background and objects of interest the proposed approach, in comparison with classical approaches, provides superiority in terms of niqe quality assessment of at least 10%, brisque quality assessment of more than 20%, derivative assessments (ME and AE) – 7.5% and 1%, respectively. The analysis of potential areas of interest details based on the processed images visualization results is the best for the combined approach in all cases. At the same time, the study provides an answer to the best combination of edge detection operators in individual color channels and without using pre-processing methods of the original image. This allows for increased efficiency of clinical trials in making a diagnosis. https://biomedpharmajournal.org/vol18marchspledition/combined-use-of-edge-selection-operators-in-individual-color-channels-for-the-analysis-of-cytological-images-presented-in-rgb-format/ Color Channels Cytological Image Edge Detection Image Processing Medical Image Microscopic Smear RGB Format