Holistic Contrast enhancement of Carpals Ossification sites for Skeletal Age Assessment System

Pediatricians often apply bone age assessment to measure the skeletal maturity of children and to predict the future height. These discrepancies are good indicators for diagnosing growth disorders. Normally, left hand skeletal is employed in this assessment. The low quality of ossification sites of carpals deteriorates the pediatrician's visibility in inspecting the pertinent radiographic manifestations. This in turn affects the bone age assessment. Therefore, we have to enhance the quality before assessing them. Histogram equalization is one of the contrast enhancement techniques that suit this enhancement. Existing histogram equalizations, however, are confronting with problems in preserving the brightness and details as well as preventing the contrast from being over-enhanced or under-enhanced simultaneously. We propose the comprehensive histogram equalization considering all criteria of desired histogram-equalized image to produce moderately contrast enhanced carpals' ossification sites. Qualitative results show that the determining features of maturity stages have been emphasized in some of the Pareto optimized image. The improvement for Pareto optimized bi-histogram equalization is significant for all stages: 7.16%, 12.4%, 16.03%, 21.21% and 18.51%. We conclude that the Pareto optimized images able to improve the classifier accuracy that estimate the maturity stage of the carpal bones.

[1]  Haidi Ibrahim,et al.  Brightness Preserving Dynamic Histogram Equalization for Image Contrast Enhancement , 2007, IEEE Transactions on Consumer Electronics.

[2]  Juan Ignacio Arribas,et al.  A Radius and Ulna TW3 Bone Age Assessment System , 2008, IEEE Transactions on Biomedical Engineering.

[3]  David W. Coit,et al.  Multi-objective optimization using genetic algorithms: A tutorial , 2006, Reliab. Eng. Syst. Saf..

[4]  F Kainberger,et al.  Computational radiology in skeletal radiography. , 2009, European journal of radiology.

[5]  K. Ramar,et al.  Histogram Modified Local Contrast Enhancement for mammogram images , 2011, Appl. Soft Comput..

[6]  Y. Y. Tan,et al.  Recursive sub-image histogram equalization applied to gray scale images , 2007, Pattern Recognit. Lett..

[7]  Chao Wang,et al.  Brightness preserving histogram equalization with maximum entropy: a variational perspective , 2005, IEEE Trans. Consumer Electron..

[8]  Concetto Spampinato,et al.  An Automatic System for Skeletal Bone Age Measurement by Robust Processing of Carpal and Epiphysial/Metaphysial Bones , 2010, IEEE Transactions on Instrumentation and Measurement.

[9]  P M Kemp,et al.  Bone age assessment: a large scale comparison of the Greulich and Pyle, and Tanner and Whitehouse (TW2) methods , 1999, Archives of disease in childhood.

[10]  Nor Ashidi Mat Isa,et al.  Quadrants dynamic histogram equalization for contrast enhancement , 2010, IEEE Transactions on Consumer Electronics.

[11]  John D. Austin,et al.  Adaptive histogram equalization and its variations , 1987 .

[12]  A. Bovik,et al.  A universal image quality index , 2002, IEEE Signal Processing Letters.

[13]  P. Rajavel,et al.  Image dependent brightness preserving histogram equalization , 2010, IEEE Transactions on Consumer Electronics.

[14]  Yeong-Taeg Kim,et al.  Contrast enhancement using brightness preserving bi-histogram equalization , 1997 .

[15]  Haidi Ibrahim,et al.  Bi-histogram equalization with a plateau limit for digital image enhancement , 2009, IEEE Transactions on Consumer Electronics.

[16]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[17]  Aifeng Zhang,et al.  Automatic bone age assessment for young children from newborn to 7-year-old using carpal bones , 2007, Comput. Medical Imaging Graph..

[18]  Bülent Sankur,et al.  Statistical evaluation of image quality measures , 2002, J. Electronic Imaging.

[19]  Soong-Der Chen,et al.  A new image quality measure for assessment of histogram equalization-based contrast enhancement techniques , 2012, Digit. Signal Process..

[20]  Kalyanmoy Deb,et al.  Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms , 1994, Evolutionary Computation.

[21]  Abd. Rahman Ramli,et al.  Minimum mean brightness error bi-histogram equalization in contrast enhancement , 2003, IEEE Trans. Consumer Electron..

[22]  Abd. Rahman Ramli,et al.  Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation , 2003, IEEE Trans. Consumer Electron..

[23]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[24]  Qian Chen,et al.  Image enhancement based on equal area dualistic sub-image histogram equalization method , 1999, IEEE Trans. Consumer Electron..

[25]  Yi-Hong Chou,et al.  Computerized geometric features of carpal bone for bone age estimation. , 2007, Chinese medical journal.