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.
Crooks
I
I
Department of Radiation Oncology, McGill University, Montreal, Canada.
Fallone
B G
BG
D000465:Algorithms; D055592:Biophysical Phenomena; D001703:Biophysics; D001842:Bone and Bones / Q000000981:diagnostic imaging; D005069:Evaluation Studies as Topic; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008279:Magnetic Resonance Imaging; D011857:Radiographic Image Interpretation, Computer-Assisted; D011877:Radionuclide Imaging; D011880:Radiotherapy Planning, Computer-Assisted