Integration of computer assisted bone age assessment with clinical PACS.

Computer assisted bone age assessment (BAA) integrated with a clinical PACS is described. The image analysis is performed on a DICOM compliant workstation able to accept images from a PACS server or directly from an image modality (digital radiography or film scanner). Images can be processed in two modes. If the image is acquired from a normally developed subject, it can be added to the digital hand atlas. An image may also be subjected only to a diagnostic analysis for the BAA without archiving the features in the database. The image analysis is performed in three steps. A location of six region of interest is followed by their segmentation and feature extraction. The features analysis results in retrieving the closest image match from the standard database. Based on currently analyzed image data in the hand atlas, the standard deviation of the assessment bone age does not exceed 1 yr of age.

[1]  N. Finby,et al.  Endocrine significance of short metacarpals. , 1959, The Journal of clinical endocrinology and metabolism.

[2]  S Katsuragawa,et al.  Image feature analysis and computer-aided diagnosis in digital radiography: effect of digital parameters on the accuracy of computerized analysis of interstitial disease in digital chest radiographs. , 1990, Medical physics.

[3]  H. K. Huang,et al.  Computer-assisted bone age assessment: image preprocessing and epiphyseal/metaphyseal ROI extraction , 2001, IEEE Transactions on Medical Imaging.

[4]  J M Tanner,et al.  Automatic Bone Age Measurement Using Computerized Image Analysis , 1994, The Journal of pediatric endocrinology.

[5]  Paul Scheunders,et al.  Statistical texture characterization from discrete wavelet representations , 1999, IEEE Trans. Image Process..

[6]  H. K. Huang,et al.  Digital hand atlas for web-based bone age assessment: system design and implementation , 2000, Medical Imaging.

[7]  J KOSOWICZ,et al.  THE ROENTGEN APPEARANCE OF THE HAND AND WRIST IN GONADAL DYSGENESIS. , 1965, The American journal of roentgenology, radium therapy, and nuclear medicine.

[8]  Thrasyvoulos N. Pappas An adaptive clustering algorithm for image segmentation , 1992, IEEE Trans. Signal Process..

[9]  W. Greulich,et al.  Radiographic Atlas of Skeletal Development of the Hand and Wrist , 1999 .

[10]  F E Johnston,et al.  The contribution of the carpal bones to the assessment of skeletal age. , 1965, American journal of physical anthropology.

[11]  Ebrahim Mamdani,et al.  Applications of fuzzy algorithms for control of a simple dynamic plant , 1974 .

[12]  A. Poznanski,et al.  Metacarpophalangeal pattern profiles in the evaluation of skeletal malformations. , 1972, Radiology.

[13]  I.W. Ricketts,et al.  Classification of hand bones for bone age assessment , 1996, Proceedings of Third International Conference on Electronics, Circuits, and Systems.

[14]  Michael F. McNitt-Gray,et al.  Adding intelligence to PACS , 1992 .

[15]  Ewa Pietka Image standardization in PACS , 2000 .

[16]  Donald R. Kirks,et al.  Practical pediatric imaging: Diagnostic radiology of infants and children , 1984 .

[17]  C A Mistretta,et al.  Conventional chest radiography vs dual-energy computed radiography in the detection and characterization of pulmonary nodules. , 1994, AJR. American journal of roentgenology.

[18]  H. K. Huang,et al.  Computer Automated Approach to the Extraction of Epiphyseal Regions in Hand Radiographs , 2001, Journal of Digital Imaging.

[19]  K Doi,et al.  Image feature analysis and computer-aided diagnosis in digital radiography: automated delineation of posterior ribs in chest images. , 1991, Medical physics.

[20]  Donald B. Darling Radiography of infants and children , 1971 .

[21]  A. Gertych An automated segmentation and features extraction from hand radiographs , 2003 .

[22]  D. Chakraborty Image intensifier distortion correction. , 1987, Medical physics.

[23]  H K Huang,et al.  Image Preprocessing for a Picture Archiving and Communication System , 1992, Investigative radiology.

[24]  David F. Merten,et al.  Practical Pediatric Imaging , 1992 .

[25]  N Nakamori,et al.  Effect of heart-size parameters computed from digital chest radiographs on detection of cardiomegaly. Potential usefulness for computer-aided diagnosis. , 1991, Investigative radiology.

[26]  A Albanese,et al.  The use of a computerized method of bone age assessment in clinical practice. , 1995, Hormone research.

[27]  William J. Dallas,et al.  Digital image enhancement for display of bone radiographs , 1992, Medical Imaging.

[28]  K Doi,et al.  The nature and subtlety of abnormal findings in chest radiographs. , 1991, Medical physics.

[29]  S Katsuragawa,et al.  Image feature analysis and computer-aided diagnosis in digital radiography: detection and characterization of interstitial lung disease in digital chest radiographs. , 1988, Medical physics.

[30]  James M. Tanner,et al.  Assessment of skeletal maturity and prediction of adult height : (TW2 method) , 1986 .

[31]  Julius T. Tou,et al.  Pattern Recognition Principles , 1974 .

[32]  Stéphane Mallat,et al.  Characterization of Signals from Multiscale Edges , 2011, IEEE Trans. Pattern Anal. Mach. Intell..

[33]  G T Barnes,et al.  Scanning slit chest radiography: a practical and efficient scatter control design. , 1994, Radiology.