A novel algorithm for the edge detection and edge enhancement of medical images.

A novel algorithm, histogram shifting (HS) is presented, which performs edge detection or edge enhancement with the choice of two parameters. The histogram of a region surrounding each pixel is found and translated toward the origin, resulting in the new pixel value. Images from a variety of medical imaging modalities were processed with HS to perform detection and enhancement of edges. Comparison with results obtained from conventional edge detection (e.g., Sobel) and with conventional edge‐enhancement algorithms is discussed. HS appears to perform the edge‐detection operation without introducing ‘‘double‐edge’’ effects often obtained with conventional edge‐detection algorithms. HS also appears to perform edge enhancement without introducing extensive noise artifacts, which may be noticeable with many edge‐enhancement algorithms.