3D Adaptive Histogram Equalization Method for Medical Volumes

Medical imaging plays a fundamental role in the diagnosis and treatment of several diseases, enabling the visualization of internal organs and tissues for use in clinical procedures. The quality of medical images can be degraded by several factors, such as noise and poor contrast. The application of filtering and contrast enhancement techniques is usually necessary to improve the quality of images, which facilitates the segmentation and classification stages. In this paper, we develop and analyze a novel three-dimensional adaptive histogram equalization method for improving contrast in the context of medical imaging. Several data sets are used to demonstrate the effectiveness of the proposed approach.