A Survey on Various Kinds of Image Segmentation of Cancer Images Using Fuzzy Image Processing Methods

This essay examines several cancer forms and their segmentation strategies. An especially common death factors nowadays is cancer. Early identification and precise detection of potentially malignant nodules will improve the effectiveness of treatment and lower cancer-related mortality. The lack of obvious signs before the cancer has spread is a major impediment to identification. Potential remedies include photographing outside of invoices methodology like computed tomography (CT) and magnetic resonance picturing (MRI) for diagnosis and screening. However, in order to fully utilise the promise of this method, accurate automated analysis of these fast, high-resolution photos is required.An essential step in the process is image segmentation. The maximum and minimum values in each row and column are used in fuzzy-based picture segmentation algorithms. Based on certain image properties such pixel intensity values, colour, textures, etc., there are numerous image segmentation approaches that aid in image processing to detect distinct cancer nodules. The ideal segmentation of cancer images can now be found by combining certain techniques with intuitionistic fuzzy sets.