A contrast correction method for dental images based on histogram registration.
Contrast correction is often required in digital subtraction radiography when comparing medical data acquired over different time periods owing to dissimilarities in the acquisition process. This paper focuses on dental radiographs and introduces a novel approach for correcting the contrast in dental image pairs. The proposed method modifies the subject images by applying typical registration techniques on their histograms. The proposed histogram registration method reshapes the histograms of the two subject images in such a way that these images are matched in terms of their contrast deviation. The method was extensively tested over 4 sets of dental images, consisting of 72 registered dental image pairs with unknown contrast differences as well as 20 dental pairs with known contrast differences. The proposed method was directly compared against the well-known histogram-based contrast correction method. The two methods were qualitatively and quantitatively evaluated for all 92 available dental image pairs. The two methods were compared in terms of the contrast root mean square difference between the reference image and the corrected image in each case. The obtained results were also verified statistically using appropriate t-tests in each set. The proposed method exhibited superior performance compared with the well-established method, in terms of the contrast root mean square difference between the reference and the corrected images. After suitable statistical analysis, it was deduced that the performance advantage of the proposed approach was statistically significant.
Economopoulos
T L
TL
School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou str., Zografos, 15780, Athens, Greece.
Asvestas
P A
PA
Matsopoulos
G K
GK
Gröndahl
K
K
Gröndahl
H-G
HG
D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000706:statistics & numerical data; D008962:Models, Theoretical; D011856:Radiographic Image Enhancement / Q000379:methods*; D019252:Radiography, Dental, Digital / Q000379:methods* / Q000706:statistics & numerical data; D013382:Subtraction Technique