Bone age assessment is a radiological procedure to evaluate a child's bone age based on his or her left-hand x-ray image.
The current standard is to match patient's hand with Greulich & Pyle hand atlas, which is outdated by 50 years and only
uses subjects from one region and one ethnicity. To improve bone age assessment accuracy for today's children, an
automated race- and gender-specific bone age assessment (BAA) system has been developed in IPILab. 1390 normal
left-hand x-ray images have been collected at Children's Hospital of Los Angeles (CHLA) to form the digital hand atlas
(DHA). DHA includes both male and female children of ages one to eighteen and of four ethnic groups: African
American, Asian American, Caucasian, and Hispanic. In order to apply DHA and BAA CAD into a clinical
environment, a web-based BAA CAD system and graphical user interface (GUI) has been implemented in Women and
Children's Hospital at Los Angeles County (WCH-LAC). A CAD server has been integrated in WCH's PACS
environment, and a clinical validation workflow has been designed for radiologists, who compare CAD readings with
G&P readings and determine which reading is more suited for a certain case. Readings are logged in database and
analyzed to assess BAA CAD performance in a clinical setting. The result is a successful installation of web-based BAA
CAD system in a clinical setting.
The Digital Hand Atlas in Assessment of Skeletal Development is a large-scale Computer Aided Diagnosis (CAD)
project for automating the process of grading Skeletal Development of children from 0-18 years of age. It includes a
complete collection of 1,400 normal hand X-rays of children between the ages of 0-18 years of age. Bone Age
Assessment is used as an index of skeletal development for detection of growth pathologies that can be related to
endocrine, malnutrition and other disease types. Previous work at the Image Processing and Informatics Lab (IPILab)
allowed the bone age CAD algorithm to accurately assess bone age of children from 1 to 16 (male) or 14 (female) years
of age using the Phalanges as well as the Carpal Bones. At the older ages (16(male) or 14(female) -19 years of age) the
Phalanges as well as the Carpal Bones are fully developed and do not provide well-defined features for accurate bone
age assessment. Therefore integration of the Radius Bone as a region of interest (ROI) is greatly needed and will
significantly improve the ability to accurately assess the bone age of older children. Preliminary studies show that an
integrated Bone Age CAD that utilizes the Phalanges, Carpal Bones and Radius forms a robust method for automatic
bone age assessment throughout the entire age range (1-19 years of age).
Bone age assessment (BAA) of children is a clinical procedure frequently performed in pediatric radiology
to evaluate the stage of skeletal maturation based on a left hand and wrist radiograph. The most commonly
used standard: Greulich and Pyle (G&P) Hand Atlas was developed 50 years ago and exclusively based on
Caucasian population. Moreover, inter- & intra-observer discrepancies using this method create a need of
an objective and automatic BAA method. A digital hand atlas (DHA) has been collected with 1,400 hand
images of normal children from Asian, African American, Caucasian and Hispanic descends. Based on
DHA, a fully automatic, objective computer-aided-diagnosis (CAD) method was developed and it was
adapted to specific population. To bring DHA and CAD method to the clinical environment as a useful tool
in assisting radiologist to achieve higher accuracy in BAA, a web-based system with direct connection to a
clinical site is designed as a novel clinical implementation approach for online and real time BAA. The
core of the system, a CAD server receives the image from clinical site, processes it by the CAD method and
finally, generates report. A web service publishes the results and radiologists at the clinical site can review
it online within minutes. This prototype can be easily extended to multiple clinical sites and will provide
the foundation for broader use of the CAD system for BAA.
Bone age assessment is most commonly performed with the use of the Greulich and Pyle (G&P)
book atlas, which was developed in the 1950s. The population of theUnited States is not as
homogenous as the Caucasian population in the Greulich and Pyle in the 1950s, especially in the
Los Angeles, California area. A digital hand atlas (DHA) based on 1,390 hand images of children
of different racial backgrounds (Caucasian, African American, Hispanic, and Asian) aged 0-18
years was collected from Children's Hospital Los Angeles. Statistical analysis discovered
significant discrepancies exist between Hispanic and the G&P atlas standard. To validate the usage
of DHA as a clinical standard, diagnostic radiologists performed reads on Hispanic pediatric hand
and wrist computed radiography images using either the G&P pediatric radiographic atlas or the
Children's Hospital Los Angeles Digital Hand Atlas (DHA) as reference. The order in which the
atlas is used (G&P followed by DHA or vice versa) for each image was prepared before actual
reading begins. Statistical analysis of the results was then performed to determine if a discrepancy
exists between the two readings.
The most commonly used method for bone age assessment in clinical practice is the book atlas matching method
developed by Greulich and Pyle in the 1950s. Due to changes in both population diversity and nutrition in the United
States, this atlas may no longer be a good reference. An updated data set becomes crucial to improve the bone age
assessment process. Therefore, a digital hand atlas was built with 1,100 children hand images, along with patient
information and radiologists' readings, of normal Caucasian (CAU), African American (BLK), Hispanic (HIS), and
Asian (ASI) males (M) and females (F) with ages ranging from 0 - 18 years. This data was collected from Childrens'
Hospital Los Angeles. A computer-aided-diagnosis (CAD) method has been developed based on features extracted from
phalangeal regions of interest (ROIs) and carpal bone ROIs from this digital hand atlas. Using the data collected along
with the Greulich and Pyle Atlas-based readings and CAD results, this paper addresses this question: "Do different
ethnicities and gender have different bone growth patterns?" To help with data analysis, a novel web-based visualization
tool was developed to demonstrate bone growth diversity amongst differing gender and ethnic groups using data
collected from the Digital Atlas. The application effectively demonstrates a discrepancy of bone growth pattern amongst
different populations based on race and gender. It also has the capability of helping a radiologist determine the
normality of skeletal development of a particular patient by visualizing his or her chronological age, radiologist reading,
and CAD assessed bone age relative to the accuracy of the P&G method.
A computer-aided-diagnosis (CAD) method has been previously developed based on features extracted from phalangeal
regions of interest (ROI) in a digital hand atlas, which can assess bone age of children from ages 7 to 18 accurately.
Therefore, in order to assess the bone age of children in younger ages, the inclusion of carpal bones is necessary. In this
paper, we developed and implemented a knowledge-based method for fully automatic carpal bone segmentation and
morphological feature analysis. Fuzzy classification was then used to assess the bone age based on the selected features.
Last year, we presented carpal bone segmentation algorithm. This year, research works on procedures after carpal bone
segmentation including carpal bone identification, feature analysis and fuzzy system for bone age assessment is
presented. This method has been successfully applied on all cases in which carpal bones have not overlapped. CAD
results of total about 205 cases from the digital hand atlas were evaluated against subject chronological age as well as
readings of two radiologists. It was found that the carpal ROI provides reliable information in determining the bone age
for young children from newborn to 7-year-old.
Determination of bone age assessment (BAA) in pediatric radiology is a task based on detailed analysis of
patient's left hand X-ray. The current standard utilized in clinical practice relies on a subjective comparison
of the hand with patterns in the book atlas. The computerized approach to BAA (CBAA) utilizes automatic
analysis of the regions of interest in the hand image. This procedure is followed by extraction of quantitative
features sensitive to skeletal development that are further converted to a bone age value utilizing knowledge
from the digital hand atlas (DHA). This also allows providing BAA results resembling current clinical approach.
All developed methodologies have been combined into one CAD module with a graphical user interface (GUI).
CBAA can also improve the statistical and analytical accuracy based on a clinical work-flow analysis. For this
purpose a quality assurance protocol (QAP) has been developed. Implementation of the QAP helped to make
the CAD more robust and find images that cannot meet conditions required by DHA standards. Moreover, the
entire CAD-DHA system may gain further benefits if clinical acquisition protocol is modified. The goal of this
study is to present the performance improvement of the overall CAD-DHA system with QAP and the comparison
of the CAD results with chronological age of 1390 normal subjects from the DHA. The CAD workstation can
process images from local image database or from a PACS server.
A computer-aided-diagnosis (CAD) method has been previously developed in our Laboratory based on features
extracted from regions of interest (ROI) in phalanges in a digital hand atlas. Due to various factors, including, the
diversity of size, shape and orientation of carpal bones, non-uniformity of soft tissue, low contrast between the bony
structure and soft tissue, the automatic identification and segmentation of bone boundaries is an extremely
challenging task. Past research work on carpal bone segmentation has been done utilizing dynamic thresholding.
However, due to the discrepancy of carpal bones developments and the limitations of segmentation algorithms,
carpal bone ROI has not been taken into consideration in the bone age assessment procedure. In this paper, we
present a method for fully automatic carpal bone segmentation and feature analysis in hand X-ray radiograph. The
purpose of this paper is to automatically segment the carpal bones by anisotropic diffusion and Canny edge
detection techniques. By adding their respective features extracted from carpal bones ROI to the phalangeal ROI
feature space, the accuracy of bone age assessment can be improved especially when the image processing in the
phalangeal ROI fails in younger children.
We have collected a digital hand atlas containing digitized left hand radiographs of normally developed children grouped accordingly by age, sex, and race. A set of features stored in a database reflecting patient's stage of skeletal development has been calculated by automatic image processing procedures. This paper addresses a new concept, "average" image in the digital hand atlas. The "average" reference image in the digital atlas is selected for each of the groups of normal developed children with the best representative skeletal maturity based on bony features. A data mining procedure was designed and applied to find the average image through average feature vector matching. It also provides a temporary solution for the missing feature problem through polynomial regression. As more cases are added to the digital hand atlas, it can grow to provide clinicians accurate reference images to aid the bone age assessment process.
Bone age assessment is a procedure performed in pediatric patients to quickly evaluate parameters of maturation and growth from a left hand and wrist radiograph. Pietka and Cao have developed a Computer-aided diagnosis (CAD) method of bone age assessment based on a digital hand atlas. The aim of this paper is to extend their work by automatically select the best representative image from a group of normal children based on specific bony features that reflect skeletal maturity. The group can be of any ethnic origin and gender from one year to 18 year old in the digital atlas. This best representative image is defined as the "average" image of the group that can be augmented to Piekta and Cao's method to facilitate in the bone age assessment process.