Adaptive Thresholding based on SOM Technique for Semi-Automatic NPC Image Segmentation

This paper studies Self-Organizing Map (SOM) based adaptive thresholding technique for semi-automatic image segmentation. CT images of patients with nasopharyngeal carcinoma are considered in the study. The thresholds are determined from histogram of a topological map created from SOM method. With this proposed technique, initial tumor pixel must be manually selected. Pixels which are in the same threshold level are considered as tumor pixels. The experimental results showed that our proposed technique is effective for NPC image segmentation. In addition, it can properly handle tumor heterogeneity generally found in the NPC images.