Integration of computer assisted bone age assessment with clinical PACS

Piętka, Ewa; Pospiech-Kurkowska, Sylwia; Gertych, Arkadiusz; Cao, Fei

doi:10.1016/s0895-6111(02)00076-9

Cited by 70 publications

(41 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In addition, while the integration of CAD into a routine clinical PACS environment is gaining momentum [25][26][27][28], the interactive functionality for reviewing CAD marks within PACS is currently limited. The main purpose of the present report, therefore, has been to assess the impact on reader's identification of solid lung nodules employing a CAD server integrated into a PACS environment as a potential component of routine clinical CT interpretation.…”

Section: Discussionmentioning

confidence: 99%

Impact of a Computer-Aided Detection (CAD) System Integrated into a Picture Archiving and Communication System (PACS) on Reader Sensitivity and Efficiency for the Detection of Lung Nodules in Thoracic CT Exams

Bogoni

Alpert

et al. 2012

J Digit Imaging

View full text Add to dashboard Cite

Section: Discussionmentioning

confidence: 99%

Impact of a Computer-Aided Detection (CAD) System Integrated into a Picture Archiving and Communication System (PACS) on Reader Sensitivity and Efficiency for the Detection of Lung Nodules in Thoracic CT Exams

Bogoni

Alpert

et al. 2012

J Digit Imaging

View full text Add to dashboard Cite

“…In the later stage the gap between epiphysis and metaphysis starts disappearing and fusion begins. It continues until fusion is completed and one adult bone is found [10]. In the studies that have been conducted to date, the identification of the necessary characteristics (such as the boundaries of the bones) prior to bone age assessments was performed through the use of various methods.…”

Section: Computer-assisted Bone Age Assessment Systemsmentioning

confidence: 99%

“…A computer-aided system to estimate bone age based on Fourier analysis was assessed by reference to the original radiographs used to produce the Tanner-Whitehouse 2 (TW2) standards for the radius, ulna and short finger bones [12]. In Reference [10], an approach based on wavelet processing for extracting carpal bones that are fused is proposed. De Luis Garcia detecting bone contours from hand radiographs using active contours [13].…”

Section: Computer-assisted Bone Age Assessment Systemsmentioning

confidence: 99%

Methods Used in Computer-Assisted Bone Age Assessment of Children

Aydoğdu¹,

Başçiftçi²

2014

JACN

View full text Add to dashboard Cite

Abstract-For many years, various studies have been conducted to determine methods to identify the age of living persons. Nowadays, the method most commonly used for the identification of age is bone age assessment. Bone age assessment is a method that is very frequently used in forensic cases and by child development specialists. However, the decision process in these assessments depends on the observations of a specialist; hence, the assessment results may vary from one specialist to another. The purpose of automatic assessment with computers is to render the decision process more objective, and to consequently allow more consistent results to be obtained. Studies in this area have drawn considerable attention to automatic assessment methods, especially following the developments in the area of image processing. In the current study, the Greulich-Pyle (GP) and the Tanner-Whitehouse (TW) methods used in computer-assisted bone age assessment were presented, and information was also provided regarding the automation of these methods.Index Terms-Bone age assessment, Greulich-Pyle method, Tanner-Whitehouse method, TW3. I. INTRODUCTIONIn medicine, the identification of bone age is used for the diagnosis, follow-up and treatment of diseases and endocrine disorders. It is also important in judiciary cases for establishing whether individuals are adults and have legal capacity. For example, Turkish laws and regulations divide individuals into different age groups from both a legal and penal perspective. Depending of the nature of the crime, a sentence or penalty may vary according the age group of the perpetrator. It is especially important to determine whether the individual in question is at least 7, 12, 15, or 18 years of age [1], [2].In growing individuals, the bone age is the most commonly used criterion of biological growth and age. Bone age assessments are based on studying the stages of growth associated with skeletal development through the evaluation of hand and wrist radiographies. The level of skeletal maturity can, essentially, be determined based on two characteristics: The level of growth in areas undergoing ossification, and the level of calcium accumulation in those areas. From infancy to adulthood, these two characteristics follow a certain and specific pattern and timeline [3].Studies performed from the beginning of the 20 th century to the present have made use of left hand and wrist radiographies Manuscript received June 15, 2013; revised October 16, 2013 for assessment purposes. There are certain advantages associated with using only the left hand instead of both hands. In particular, using one hand reduces both the cost of procedures and the person's exposure to radiation by half. The fact that the left hand has lower chances of experiencing accidents and injury due to the higher prevalence of right-handedness in most societies, and the fact that researchers performing the initial studies on bone age assessment preferred using the left hand are the leading reasons why the left hand is employed in ...

show abstract

“…The method presents high accuracy on its three steps: the detection of phalangeal tip, the extraction of EMROIs and the location of diameters and lower edges of EMROIs [10]. Pietka's work was extended in [11] including a wavelet decomposition to assess the fusion between the epiphyses and metaphyses. The performance of the system proposed by Pietka et al [11] has been tested in a normal (bone age equal to chronological age) population of 115 boys and 116 girls with ages from 1 to 19 years of age.…”

Section: Introductionmentioning

confidence: 99%

“…Pietka's work was extended in [11] including a wavelet decomposition to assess the fusion between the epiphyses and metaphyses. The performance of the system proposed by Pietka et al [11] has been tested in a normal (bone age equal to chronological age) population of 115 boys and 116 girls with ages from 1 to 19 years of age. The average difference of evaluated bone age and chronological age error was 0.94 years in boys and 1.13 years in girls [11].…”

Section: Introductionmentioning

confidence: 99%

Impact of Ensemble Learning in the Assessment of Skeletal Maturity

et al. 2014

View full text Add to dashboard Cite

The assessment of the bone age, or skeletal maturity, is an important task in pediatrics that measures the degree of maturation of children's bones. Nowadays, there is no standard clinical procedure for assessing bone age and the most widely used approaches are the Greulich and Pyle and the Tanner and Whitehouse methods. Computer methods have been proposed to automatize the process; however, there is a lack of exploration about how to combine the features of the different parts of the hand, and how to take advantage of ensemble techniques for this purpose. This paper presents a study where the use of ensemble techniques for improving bone age assessment is evaluated. A new computer method was developed that extracts descriptors for each joint of each finger, which are then combined using different ensemble schemes for obtaining a final bone age value. Three popular ensemble schemes are explored in this study: bagging, stacking and voting. Best results were achieved by bagging with a rule-based regression (M5P), scoring a mean absolute error of 10.16 months. Results show that ensemble techniques improve the prediction performance of most of the evaluated regression algorithms, always achieving best or comparable to best results. Therefore, the success of the ensemble methods allow us to conclude that their use may improve computer-based bone age assessment, offering a scalable option for utilizing multiple regions of interest and combining their output.

show abstract

Integration of computer assisted bone age assessment with clinical PACS

Cited by 70 publications

References 20 publications

Impact of a Computer-Aided Detection (CAD) System Integrated into a Picture Archiving and Communication System (PACS) on Reader Sensitivity and Efficiency for the Detection of Lung Nodules in Thoracic CT Exams

Impact of a Computer-Aided Detection (CAD) System Integrated into a Picture Archiving and Communication System (PACS) on Reader Sensitivity and Efficiency for the Detection of Lung Nodules in Thoracic CT Exams

Methods Used in Computer-Assisted Bone Age Assessment of Children

Impact of Ensemble Learning in the Assessment of Skeletal Maturity

Contact Info

Product

Resources

About