Review of cell detection approaches in intelligent systems for antinuclear factor determination

This paper reviews modern approaches for cell detection and segmentation in medical images aimed at determining antinuclear factors. Articles focused on the use of intelligent technologies for antinuclear factor determination are analyzed. The application of segmentation methods, such as watershed transformation, Otsu’s method, clustering algorithms and neural networks, in image processing tasks is investigated. The main approaches to the development of automated systems for classifying the images of individual cells in medical images are highlighted. The current state of technological advancements and their potential to enhance the accuracy and reliability of medical diagnostics are assessed.