Aifeng Zhang

Automatic bone age assessment for young children from newborn to 7-year-old using carpal bones.

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. However, due to various factors including the uncertain number of bones appearing, non-uniformity of soft tissue, low contrast between the bony structure and soft tissue, automatic segmentation and identification of carpal bone boundaries is an extremely challenging task. Past research works on carpal bone segmentation were performed utilizing dynamic thresholding. However, due to the limitation of the segmentation algorithm, carpal bones have not been taken into consideration in the bone age assessment procedure. 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. 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.

Racial Differences in Growth Patterns of Children Assessed on the Basis of Bone Age

PURPOSE To collect up-to-date data in healthy children to create a digital hand atlas (DHA) that can be used to evaluate, on the basis of the Greulich and Pyle atlas method, racial differences in skeletal growth patterns of Asian, African American, white, and Hispanic children in the United States. MATERIALS AND METHODS This retrospective study was HIPAA compliant and approved by the institutional review board. Informed consent was obtained from all subjects or their guardians. From May 1997 to March 2008, a DHA containing 1390 hand and wrist radiographs obtained in male and female Asian, African American, white, and Hispanic children with normal skeletal development was developed. The age of subjects ranged from 1 day to 18 years. Each image was read by two pediatric radiologists working independently and without knowledge of the subjects chronologic age, and evaluation was based on their experience with the Greulich and Pyle atlas. Statistical analyses were performed with the paired-samples t test and analysis of variance to study racial differences in growth patterns. P <or= .05 indicated a significant difference. RESULTS Bone age (P </= .05) was significantly overestimated in Asian and Hispanic children. These children appear to mature sooner than their African American and white peers. This was seen in both male and female subjects, especially in girls aged 10-13 years and boys aged 11-15 years. CONCLUSION Ethnic and racial differences in growth patterns exist at certain ages; however, the Greulich and Pyle atlas does not recognize this fact. Assessment of bone age in children with use of the Greulich and Pyle atlas can be improved by considering the subjects ethnicity.

Data grid for large-scale medical image archive and analysis

Storage and retrieval technology for large-scale medical image systems has matured significantly during the past ten years but many implementations still lack cost-effective backup and recovery solutions. As an example, a PACS (Picture Archiving and Communication system) in a general medical center requires about 40 Terabytes of storage capacity for seven years. Despite many healthcare centers are relying on PACS for 24/7 clinical operation, current PACS lacks affordable fault-tolerance storage strategies for archive, backup, and disaster recovery. Existing solutions are difficult to administer, and often time consuming for effective recovery after a disaster. For this reason, PACS still encounters unexpected downtime for hours or days, which could cripple daily clinical service and research operations. Grid Computing represents the latest and most exciting technology to evolve from the familiar realm of parallel, peer-to-peer, and client-server models that can address the problem of fault-tolerant storage for backup and recovery of medical images. We have researched and developed a novel Data Grid testbed involving several federated PAC systems based on grid computing architecture. By integrating grid architecture to the PACS DICOM (Digital Imaging and Communication in Medicine) environment, in addition to use its own storage device, a PACS also uses a federated Data Grid composing of several PAC systems for off-site backup archive. In case its own storage fails, the PACS can retrieve its image data from the Data Grid timely and seamlessly. The design reflects the Globus Toolkit 3.0 five-layer architecture of the grid computing: Fabric, Resource, Connectivity, Collective, and Application Layers. The testbed consists of three federated PAC systems, the Fault-Tolerant PACS archive server at the Image Processing and Informatics Laboratory, the clinical PACS at Saint Johns Health Center, and the clinical PACS at the Healthcare Consultation Center II, USC Health Science Campus.In the testbed, we also implement computational services in the Data Grid for image analysis and data mining. The federated PAC systems can use this resource by sharing image data and computational services available in the Data Grid for image analysis and data mining application.In the paper, we first review PACS and its clinical operation, followed by the description of the Data Grid architecture in the testbed. Different scenarios of using the DICOM store and query/retrieve functions of the laboratory model to demonstrate the fault-tolerance features of the Data Grid are illustrated. The status of current clinical implementation of the Data Grid is reported. An example of using the digital hand atlas for bone age assessment of children is presented to describe the concept of computational services in the Data Grid.

Automated bone age assessment of older children using the radius

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 for young children from newborn to 7-year-old using carpal bones

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.

Carpal bone analysis in bone age assessment

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.

An online real-time DICOM web-based computer-aided diagnosis system for bone age assessment of children in a PACS environment

Bone age assessment is a radiological procedure to evaluate a childs bone age based on his or her left-hand x-ray image. The current standard is to match patients 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 todays 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 Childrens 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 Childrens Hospital at Los Angeles County (WCH-LAC). A CAD server has been integrated in WCHs 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.

Bone age assessment in Hispanic children: digital hand atlas compared with the Greulich and Pyle (G&P) atlas

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 Childrens 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 Childrens 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.

Web-based computer-aided-diagnosis (CAD) system for bone age assessment (BAA) of children

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.

A CAD system and quality assurance protocol for bone age assessment utilizing digital hand atlas

Determination of bone age assessment (BAA) in pediatric radiology is a task based on detailed analysis of patients 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.