AUTOMATION OF SEGMENTATION OF MEDICAL IMAGES

Abstract

The work is devoted to the software implementation of digital image processing methods, in particular, segmentation of medical images, using the advantages of the Python programming language. The work implements filtering and noise reduction algorithms, such as the fuzzy adaptive median filter, as well as segmentation using clustering methods and algorithms, such as the Otsu method and the Gabor filter for texture detection. Modifications of fuzzy C-means algorithms to improve medical data segmentation are also considered. The development of medical image segmentation scripts will automate the process of data processing and analysis in the medical field. This will help improve diagnostic accuracy, provide faster access to medical image processing results, and open up new opportunities for research and treatment planning.