Document Type
Article
Publication Date
1-1-2012
Abstract
Standard X-ray images using conventional screen-film technique have a limited field of view that is insufficient to show the full bone structure of large hands on a single frame. To produce images containing the whole hand structure, digitized images from the X-ray films can be assembled using image stitching. This paper presents a new medical image stitching method that utilizes minimum average correlation energy filters to identify and merge pairs of hand X-ray medical images. The effectiveness of the proposed method is demonstrated in the experiments involving two databases which contain a total of 40 pairs of overlapping and non-overlapping hand images. The experimental results are compared with that of the normalized cross-correlation (NCC) method. It is found that the proposed method outperforms the NCC method in classifying and merging the overlapping and non-overlapping medical images. The efficacy of the proposed method is further indicated by its average execution time, which is about five times shorter than that of the other method. © 2012 Society for Imaging Informatics in Medicine.
Keywords
Artifacts, Automation, Hand/*radiography, Humans, *Phantoms, Imaging, *Radiographic Image Enhancement, Radiographic Image Interpretation, Computer-Assisted, Radiology Information Systems/*organization & administration, Sensitivity and Specificity
Divisions
fac_eng
Publication Title
Journal of Digital Imaging
Volume
26
Issue
2
Publisher
Springer Verlag (Germany)
Additional Information
Samsudin, Salbiah Adwan, Somaya Arof, H Mokhtar, N Ibrahim, F eng Research Support, Non-U.S. Gov't 2012/05/23 06:00 J Digit Imaging. 2013 Apr;26(2):361-70. doi: 10.1007/s10278-012-9483-5.