Abstract
Whole-body bone scan is one of the most frequent diagnostic procedures in nuclear medicine. Especially, it plays a significant role in important procedures such as the diagnosis of osseous metastasis and evaluation of osseous tumor response to chemotherapy and radiation therapy. It can also be used to monitor the possibility of any recurrence of the tumor. However, it is a very time-consuming effort for radiologists to quantify subtle interval changes between successive whole-body bone scans because of many variations such as intensity, geometry, and morphology. In this paper, we present the most effective method of image enhancement based on histograms, which may assist radiologists in interpreting successive whole-body bone scans effectively. Forty-eight successive whole-body bone scans from 10 patients were obtained and evaluated using six methods of image enhancement based on histograms: histogram equalization, brightness-preserving bi-histogram equalization, contrast-limited adaptive histogram equalization, end-in search, histogram matching, and exact histogram matching (EHM). Comparison of the results of the different methods was made using three similarity measures peak signal-to-noise ratio, histogram intersection, and structural similarity. Image enhancement of successive bone scans using EHM showed the best results out of the six methods measured for all similarity measures. EHM is the best method of image enhancement based on histograms for diagnosing successive whole-body bone scans. The method for successive whole-body bone scans has the potential to greatly assist radiologists quantify interval changes more accurately and quickly by compensating for the variable nature of intensity information. Consequently, it can improve radiologists’ diagnostic accuracy as well as reduce reading time for detecting interval changes.












Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Doi K: Computer-aided diagnosis in medical imaging: historical review, current status and future potential. Comput Med Imaging Graph 31:198–211, 2007
Shiraishi J, Li Q, Appelbaum D, Pu Y, Doi K: Development of a computer-aided diagnostic scheme for detection of interval changes in successive whole-body bone scans. Med Phys 34:25–36, 2007
Shiraishi J, Appelbaum D, Pu Y, Li Q, Pesce L, Doi K: Usefulness of temporal subtraction images for identification of interval changes in successive whole-body bone scans: JAFROC analysis of radiologists’ performance. Acad Radiol 14:959–966, 2007
Jia-Yann H, Pan-Fu K, Yung-Sheng C: A set of image processing algorithms for computer-aided diagnosis in nuclear medicine whole body bone scan images. Nuclear Science, IEEE Transactions on 54:514–522, 2007
Tang-Kai Y, Nan-Tsing C: A computer-aided diagnosis for locating abnormalities in bone scintigraphy by a fuzzy system with a three-step minimization approach. Medical Imaging, IEEE Transactions on 23:639–654, 2004
Sajn L, Kukar M, Kononenko I, Milcinski M: Computerized segmentation of whole-body bone scintigrams and its use in automated diagnostics. Comput Methods Programs Biomed 80:47–55, 2005
Sadik M, Jakobsson D, Olofsson F, Ohlsson M, Suurkula M, Edenbrandt L: A new computer-based decision-support system for the interpretation of bone scans. Nucl Med Commun 27:417–423, 2006
Gonzalez R, Woods R: Digital image processing, 3rd edition. Prentice-Hall, Englewood Cliffs, 2007
Yeong-Taeg K: Contrast enhancement using brightness preserving bi-histogram equalization. Consumer Electronics, IEEE Transactions on 43:1–8, 1997
Zuiderveld K: Contrast Limited Adaptive Histogram Equalization. Academic, New York, 1994
Coltuc D, Bolon P, Chassery JM: Exact histogram specification. Image Processing, IEEE Transactions on 15:1143–1152, 2006
Swain MJ, Ballard DH: Color indexing. Int J Comput Vis 7:11–32, 1991
Zhou W, Bovik AC, Sheikh HR, Simoncelli EP: Image quality assessment: from error visibility to structural similarity. Image Processing, IEEE Transactions on 13:600–612, 2004
Acknowledgments
This work was supported by the Korea Research Foundation Grant funded by the Korean Government (KRF-2007-313-D00969) and research grant support from the National Cancer Center, Korea (0910070).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Jeong, C.B., Kim, K.G., Kim, T.S. et al. Comparison of Image Enhancement Methods for the Effective Diagnosis in Successive Whole-Body Bone Scans. J Digit Imaging 24, 424–436 (2011). https://doi.org/10.1007/s10278-010-9273-x
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10278-010-9273-x