Biomedical subjects

E Pietka

Publications and source records attributed to E Pietka.

10 recordsLinked to original sources

PubMed2001

Computer-assisted bone age assessment: image preprocessing and epiphyseal/metaphyseal ROI extraction.

Clinical assessment of skeletal maturity is based on a visual comparison of a left-hand wrist radiograph with atlas patterns. Using a new digital hand atlas an image analysis methodology is being developed. To assist radiologists in bone age estimation. The analysis starts with a preprocessing function yielding epiphyseal/metaphyseal regions of interest (EMROIs). Then, these regions are subjected to a feature extraction function. Accuracy has been measured independently at three stages of the image analysis: detection of phalangeal tip, extraction of the EMROIs, and location of diameters and lower edge of the EMROIs. Extracted features describe the stage of skeletal development more objectively than visual comparison.

Adolescent↗

PubMed2001

Skeletal age determinations in children of European and African descent: applicability of the Greulich and Pyle standards.

This study assesses the value of the Greulich and Pyle method in determining the skeletal ages of healthy American children of European and African descent born after the year 1980. The hand and wrist radiographs of 534 children (265 boys, 269 girls; 260 European-Americans [EA], 274 African-Americans [AA]), ages 0 to 19 y, were analyzed by two experienced pediatric radiologists blinded to the chronological age of the subjects. A difference score was calculated for each subject by subtracting chronological age from the mean bone ages scores provided by the two raters. One group t-tests were performed to verify the hypothesis that the mean difference score was equal to zero. Skeletal age determinations by the two radiologists showed a high degree of agreement by intraclass correlation coefficient (r = 0.994). The range of values for differences in skeletal and chronological ages was very wide, indicating great individual variability. Comparisons between skeletal and chronological age only reached statistical significance in EA prepubertal girls, whose skeletal ages were delayed, on average, by three months (t = -2.9; p = 0.005). Mean difference between skeletal and chronological age in prepubertal children of African descent was 0.09 +/- 0.66 y, while that in children of European descent was -0.17 +/- 0.67 y; (t = 3.13; p = 0.0019). On average, the bone ages of 10% of all prepubertal AA children were 2 SD above the normative data in the Greulich and Pyle atlas, while the bone ages of 8% of all prepubertal EA children were 2 SD below. In contrast to the racial differences observed in prepubertal children, EA postpubertal males had significantly greater values for bone age than AA postpubertal males (t = 2.03; p = 0.05). In conclusion, variations in skeletal maturation in prepubertal children are greater than those reflected in the Greulich and Pyle atlas; prepubertal American children of European descent have significantly delayed skeletal maturation when compared with those of African descent; and, postpubertal EA males have significantly advanced skeletal maturation when compared with postpubertal AA males. New standards are needed to make clinical decisions that require reliable bone ages and to accurately represent a multiethnic pediatric population.

Adolescent↗

PubMed1994

Lung segmentation in digital radiographs.

Computer-assisted interpretation of computer radiography (CR) chest images including lung nodules detection, quantitative texture analysis, etc requires a lung delineation algorithm that restricts the area to be analyzed. This report presents a new lung-segmentation technique. It is performed in three phases. First, a histogram analysis finds a threshold value that eliminates the densest anatomic regions. Then, a gradient analysis separates the lungs from parts of thorax attached to the lungs that have not been removed in the previous phase. A smoothing routine yields the final image. By imposing a testing condition that results from the histogram analysis, underexposed images are not being considered. If being segmented, they exhibit a significant lung penetration. The test increases the accuracy of the procedure and makes it safer for an unsupervised application. The segmentation procedure has been implemented together with preprocessing functions in our clinical picture archiving and communication system.

Algorithms↗

PubMed1992

Orientation correction for chest images.

This report presents an automatic procedure that determines the orientation of computed radiography (CR) chest images and rotates them to a standard position to be viewed by radiologists. As an input, CR images of a normalized size of 1,000 x 1,000 or 2,000 x 2,000 pixels are used. The analysis is performed in three steps. First, the orientation of the spine within the image is determined. Then, a function searches for upper extremities and the subdiaphragm. Finally, the lungs are extracted and their areas are compared. This indicates whether the image needs to be y-axis flipped. These three steps set the value of three parameters on the basis of which the final rotation angle is determined. The procedure has been implemented in the clinics at UCLA. The rate of correctly rotated images is 95.4%.

Algorithms↗

PubMed1992

Image preprocessing for a picture archiving and communication system.

OBJECTIVES AND RATIONALE: In a picture archiving and communication system (PACS), images are acquired from multiple modalities and displayed on an electronic workstation. Each modality has different image characteristics. This variability must be addressed before the image is displayed. METHODS: The authors developed methods to automatically process magnetic resonance (MR), computed tomographic (CT), and computed radiography (CR) images before display and subjectively evaluated their effectiveness. RESULTS: Unwanted background successfully was automatically removed from 89.5% of 615 CR images. Of 803 chest, abdomen, and hand images 93% were automatically rotated to the correct orientation. CONCLUSIONS: Automated preprocessing of PACS images can be performed successfully, improving speed and convenience for the radiologist interpreting images at an electronic workstation.

Image Processing, Computer-Assisted↗

PubMedDate not supplied

Correction of aberration in image-intensifier systems.

A mathematical model describing spatial distortions caused by an image intensifier has been developed. These distortions originate from projecting a flat plane onto a curved input phosphor surface. Considering the source of these distortions and their magnification along the radial distance, it is possible to describe them in terms of the geometrical relations between a point on a physical object and its projection onto an input phosphor screen's spherical surface. On the basis of these relations, the correction of pixel coordinates and pixel values has been performed. Parameters included in the derived formula consider the radius of curvature of the input screen, the view angle, the distance from the focal spot to the object, and the distance from the focal spot to the input phosphor screen. These parameters make the correction formula system independent and permit its application to any image projected under different view angle and/or acquired with different image-intensifier system. The correction leads to a nearly distortion-free image.

Angiography↗

PubMedDate not supplied

Computer-assisted bone age assessment based on features automatically extracted from a hand radiograph.

This paper presents a computer-aided classification algorithm to assist the radiologist in the bone age assessment of pediatric patients. The classification is based on features automatically extracted from two regions of Computed Radiography (CR) left hand wrist images: phalangeal region of interest (PROI) and carpal bone region of interest (CROI). Due to imprecise nature of the bone age assessment problem, a fuzzy classifier for both regions has been developed. After defining a membership function for each region, features are processed yielding a matrix which maps the set of features to a year of age within the predefined range. The grades of membership are described as membership function values in the interval [0, 1]. A classification rule based on a max-sum operator, processes the matrix assessing the bone age. Since both regions are analyzed independently, two bone age assessments are obtained. They reflect the phalangeal and carpal bones maturity individually. In pathological cases the discrepancy between both assessments may reach as much as 2 yr.

Age Determination by Skeleton↗

PubMedDate not supplied

Epiphyseal fusion assessment based on wavelets decomposition analysis.

Epiphyseal fusion is a finding frequently analysed in hand wrist radiographs. It is tested in the bone age assessment, the gonadal dysgenesis, etc. The computerized fusion analysis is performed on an automatically selected region of interest containing the lower edge of epiphysis and the upper edge of metaphysis. In the analysis a wavelets decomposition approach is employed. The wavelets decomposition components are first subjected to a preliminary test which rejects the overexposed images whose analysis would not give reasonable results. This increases the accuracy of the algorithm and a chance for an unsupervised application. Then, a quantitative measure is found. Its value decreases while the epiphyseal fusion proceeds. The analysis yields an assignment of fusion to one of four stages: no fusion, early stage of fusion, advanced stage of fusion, and fusion completed. The results show that wavelets decomposition components may efficiently be applied to a texture analysis.

Age Determination by Skeleton↗

PubMedDate not supplied

Digital hand atlas and web-based bone age assessment: system design and implementation.

Bone age assessment is a procedure frequently performed in pediatric patients to evaluate their growth disorder. A simple method commonly used in bone age assessment is atlas matching by a radiological examination of a left-hand radiograph against a small reference set of Greulich-Pyle atlas patterns of normal standards. The method however can lead to significant deviation in age assessment, due to a variety of observers with different levels of training. The Greulich-Pyle atlas developed in the 1950s based on middle upper class white populations, is also not fully applicable for children of today, especially regarding the standard development in other racial groups. In this paper, we present our system design and initial implementation of a digital hand atlas and computer-aided diagnostic (CAD) system for Web-based bone age assessment. The CAD system is built on top of existing picture archiving and communication system (PACS), as well as recent advances in Internet technology. It consists of a hand atlas database, a CAD module and a Java-based Web user interface. The digital atlas is based on a large new set of clinically normal hand images of diverse ethnic groups. A relational image database system is used to organize hand images, their extracted quantitative features and patient data. The digital atlas removes the disadvantages of the currently out-of-date Greulich-Pyle atlas and allows the bone age assessment to be computerized. The Java-based Web user interface allows users to interact with the hand image database from browsers. Users can use a Web browser to push a clinical hand image to the CAD server for a bone age assessment. Quantitative features on the examined image, which reflect the skeletal maturity, are then extracted and compared with patterns from the atlas database to assess the bone age. The digital atlas method based on open system Internet technology provides an alternative to supplement or replace the traditional one for a quantitative, accurate and cost-effective assessment of bone age.

Adolescent↗

PubMedDate not supplied

Medical image informatics infrastructure design and applications.

Picture archiving and communication systems (PACS) is a system integration of multimodality images and health information systems designed for improving the operation of a radiology department. As it evolves, PACS becomes a hospital image document management system with a voluminous image and related data file repository. A medical image informatics infrastructure can be designed to take advantage of existing data, providing PACS with add-on value for health care service, research, and education. A medical image informatics infrastructure (MIII) consists of the following components: medical images and associated data (including PACS database), image processing, data/knowledge base management, visualization, graphic user interface, communication networking, and application oriented software. This paper describes these components and their logical connection, and illustrates some applications based on the concept of the MIII.

Age Determination by Skeleton↗