Imaging methods: X-ray, Ct,mri,spect,pet definition: Image segmentation is a procedure for extracting the region of interest (ROI) Throughan A Utomatic or semi-automatic process "1". Application: Border detection in angiograms of coronary coronary angiography, surgical planning, simulation of surgeries, tumor detection and SE Gmentation tumor detection and segmentation, brain development Study, functional mapping, blood cells automated classification, mass detection in MA Mmograms, image registration, heart segmentation and analysis of cardiac images.
Partitioning method (class 4):
1) region-based methods, here we explain the most popular regionbased approaches:thresholding and region growing. Threshold method Disadvantage: No spatial information of the image is taken into account, resulting in noise-sensitive
Local threshold method (based on local mean variance information) and Otsu thresholding (finding optimal global threshold, minimizing intra-class variance) 1.2) Area growth method, an interactive segmentation method that produces hole or disconnected regions 2) clustering methods, 2.1) k-means2.2) (Fuzzy c-means2.3) EM algorithm 3) Classifier methods (pattern recognition), K nearest neighbor (KNN, non-parametric) and maximum likelihood (parameters), the disadvantage does not use spatial information, training data need to be manually segmented. 4) hybrid methods.4.1) Gruph cut4.2) result evaluation: Dice similarity Index (DSI) measures the degree of overlap between automatic and manual segmentation. Experimental data: Reference: "1" Norouzi, A., Rahim, M.S.M, Altameem, A., Saba, T., Rad, A.e., Rehman, A., Uddin, M., 2014. Medical Image Segmentation Methods, algorithms, and applications. Iete Technical Review 31, 199-213.
Review of segmentation for Medical image analysis
