The BoneXpert method for automated determination of skeletal maturity

Hans Henrik Thodberg; Sven Kreiborg; Anders Juul; Karen Damgaard Pedersen

doi:10.1109/TMI.2008.926067

The BoneXpert method for automated determination of skeletal maturity

Hans Henrik Thodberg, Sven Kreiborg, Anders Juul, Karen Damgaard Pedersen

Sektion 06

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › peer review

369 Citationer (Scopus)

Abstract

Udgivelsesdato: 2009-Jan

Originalsprog	Engelsk
Tidsskrift	IEEE Transactions on Medical Imaging
Vol/bind	28
Udgave nummer	1
Sider (fra-til)	52-66
Antal sider	15
ISSN	0278-0062
DOI	https://doi.org/10.1109/TMI.2008.926067
Status	Udgivet - 2009

Bibliografisk note

Keywords: Adolescent; Age Determination by Skeleton; Anthropometry; Arm; Bone Development; Bone and Bones; Child; Child, Preschool; Computer-Aided Design; Female; Hand; Humans; Image Processing, Computer-Assisted; Male; Models, Anatomic; Principal Component Analysis; Reproducibility of Results

Adgang til dokumentet

10.1109/TMI.2008.926067

Citationsformater

@article{2bb2b9c067e111df928f000ea68e967b,

title = "The BoneXpert method for automated determination of skeletal maturity",

abstract = "Bone age rating is associated with a considerable variability from the human interpretation, and this is the motivation for presenting a new method for automated determination of bone age (skeletal maturity). The method, called BoneXpert, reconstructs, from radiographs of the hand, the borders of 15 bones automatically and then computes {"}intrinsic{"} bone ages for each of 13 bones (radius, ulna, and 11 short bones). Finally, it transforms the intrinsic bone ages into Greulich Pyle (GP) or Tanner Whitehouse (TW) bone age. The bone reconstruction method automatically rejects images with abnormal bone morphology or very poor image quality. From the methodological point of view, BoneXpert contains the following innovations: 1) a generative model (active appearance model) for the bone reconstruction; 2) the prediction of bone age from shape, intensity, and texture scores derived from principal component analysis; 3) the consensus bone age concept that defines bone age of each bone as the best estimate of the bone age of the other bones in the hand; 4) a common bone age model for males and females; and 5) the unified modelling of TW and GP bone age. BoneXpert is developed on 1559 images. It is validated on the Greulich Pyle atlas in the age range 2-17 years yielding an SD of 0.42 years [0.37; 0.47] 95% conf, and on 84 clinical TW-rated images yielding an SD of 0.80 years [0.68; 0.93] 95% conf. The precision of the GP bone age determination (its ability to yield the same result on a repeated radiograph) is inferred under suitable assumptions from six longitudinal series of radiographs. The result is an SD on a single determination of 0.17 years [0.13; 0.21] 95% conf.",

author = "Thodberg, {Hans Henrik} and Sven Kreiborg and Anders Juul and Pedersen, {Karen Damgaard}",

note = "Keywords: Adolescent; Age Determination by Skeleton; Anthropometry; Arm; Bone Development; Bone and Bones; Child; Child, Preschool; Computer-Aided Design; Female; Hand; Humans; Image Processing, Computer-Assisted; Male; Models, Anatomic; Principal Component Analysis; Reproducibility of Results",

year = "2009",

doi = "10.1109/TMI.2008.926067",

language = "English",

volume = "28",

pages = "52--66",

journal = "I E E E Transactions on Medical Imaging",

issn = "0278-0062",

publisher = "Institute of Electrical and Electronics Engineers",

number = "1",

}

TY - JOUR

T1 - The BoneXpert method for automated determination of skeletal maturity

AU - Thodberg, Hans Henrik

AU - Kreiborg, Sven

AU - Juul, Anders

AU - Pedersen, Karen Damgaard

N1 - Keywords: Adolescent; Age Determination by Skeleton; Anthropometry; Arm; Bone Development; Bone and Bones; Child; Child, Preschool; Computer-Aided Design; Female; Hand; Humans; Image Processing, Computer-Assisted; Male; Models, Anatomic; Principal Component Analysis; Reproducibility of Results

PY - 2009

Y1 - 2009

N2 - Bone age rating is associated with a considerable variability from the human interpretation, and this is the motivation for presenting a new method for automated determination of bone age (skeletal maturity). The method, called BoneXpert, reconstructs, from radiographs of the hand, the borders of 15 bones automatically and then computes "intrinsic" bone ages for each of 13 bones (radius, ulna, and 11 short bones). Finally, it transforms the intrinsic bone ages into Greulich Pyle (GP) or Tanner Whitehouse (TW) bone age. The bone reconstruction method automatically rejects images with abnormal bone morphology or very poor image quality. From the methodological point of view, BoneXpert contains the following innovations: 1) a generative model (active appearance model) for the bone reconstruction; 2) the prediction of bone age from shape, intensity, and texture scores derived from principal component analysis; 3) the consensus bone age concept that defines bone age of each bone as the best estimate of the bone age of the other bones in the hand; 4) a common bone age model for males and females; and 5) the unified modelling of TW and GP bone age. BoneXpert is developed on 1559 images. It is validated on the Greulich Pyle atlas in the age range 2-17 years yielding an SD of 0.42 years [0.37; 0.47] 95% conf, and on 84 clinical TW-rated images yielding an SD of 0.80 years [0.68; 0.93] 95% conf. The precision of the GP bone age determination (its ability to yield the same result on a repeated radiograph) is inferred under suitable assumptions from six longitudinal series of radiographs. The result is an SD on a single determination of 0.17 years [0.13; 0.21] 95% conf.

AB - Bone age rating is associated with a considerable variability from the human interpretation, and this is the motivation for presenting a new method for automated determination of bone age (skeletal maturity). The method, called BoneXpert, reconstructs, from radiographs of the hand, the borders of 15 bones automatically and then computes "intrinsic" bone ages for each of 13 bones (radius, ulna, and 11 short bones). Finally, it transforms the intrinsic bone ages into Greulich Pyle (GP) or Tanner Whitehouse (TW) bone age. The bone reconstruction method automatically rejects images with abnormal bone morphology or very poor image quality. From the methodological point of view, BoneXpert contains the following innovations: 1) a generative model (active appearance model) for the bone reconstruction; 2) the prediction of bone age from shape, intensity, and texture scores derived from principal component analysis; 3) the consensus bone age concept that defines bone age of each bone as the best estimate of the bone age of the other bones in the hand; 4) a common bone age model for males and females; and 5) the unified modelling of TW and GP bone age. BoneXpert is developed on 1559 images. It is validated on the Greulich Pyle atlas in the age range 2-17 years yielding an SD of 0.42 years [0.37; 0.47] 95% conf, and on 84 clinical TW-rated images yielding an SD of 0.80 years [0.68; 0.93] 95% conf. The precision of the GP bone age determination (its ability to yield the same result on a repeated radiograph) is inferred under suitable assumptions from six longitudinal series of radiographs. The result is an SD on a single determination of 0.17 years [0.13; 0.21] 95% conf.

U2 - 10.1109/TMI.2008.926067

DO - 10.1109/TMI.2008.926067

M3 - Journal article

C2 - 19116188

VL - 28

SP - 52

EP - 66

JO - I E E E Transactions on Medical Imaging

JF - I E E E Transactions on Medical Imaging

SN - 0278-0062

IS - 1

ER -