Biomedical subjects

Ewa Pietka

Publications and source records attributed to Ewa Pietka.

3 recordsLinked to original sources

PubMed2005

Informatics infrastructure of CAD system.

A computer aided diagnosis (CAD) system requires several components which influence its effectiveness. An image processing methodology is responsible for the analysis, database structure archives and distributes the patient demographics, clinical information, and image data. A graphical user interface is applied in order to enter the data and present it to the user. By designing dynamic Web pages a remote access to the entire is granted. The computer aided diagnosis system includes three layers, which might be installed on various platforms. Elements of the application software are designed independently. Integration of all components is another issue discussed in the presented paper. Implementation of a computer aided diagnosis system improves and accelerates the analysis by giving to the user objective measurement tools. It also standardizes the decision-making process and solves the problem of replicability. Finally, it permits a set of images and features to be collected and recognized as a medical standard and be applied in education and research.

Diagnosis, Computer-Assisted↗

PubMed2004

Computer-assisted bone age assessment: graphical user interface for image processing and comparison.

The current study is part of a project resulting in a computer-assisted analysis of a hand radiograph yielding an assessment of skeletal maturity. The image analysis is based on features selected from six regions of interest. At various stages of skeletal development different image processing problems have to be addressed. At the early stage, feature extraction is based on Lee filtering followed by the random Gibbs fields and mathematical morphology. Once the fusion starts, wavelet decomposition methods are implemented. The user interface displays the closest neighbors to each image under consideration. Results show the sensitivity of different regions to both stages of development and certain feature sensitivity within each region. At the early stage of development, the distal features are more reliable indicators, whereas at the stage of epiphyseal fusion, a larger dynamic range of middle features makes them more sensitive. In the current study, a graphical user interface has been designed and implemented for testing the image processing routines and comparing the results of quantitative image analysis with the visual interpretation of extracted regions of interest. The user interface may also serve as a teaching tool. At the later stage of the project it will be used as a classification tool.

Adolescent↗

PubMed2003

Integration of computer assisted bone age assessment with clinical PACS.

Computer assisted bone age assessment (BAA) integrated with a clinical PACS is described. The image analysis is performed on a DICOM compliant workstation able to accept images from a PACS server or directly from an image modality (digital radiography or film scanner). Images can be processed in two modes. If the image is acquired from a normally developed subject, it can be added to the digital hand atlas. An image may also be subjected only to a diagnostic analysis for the BAA without archiving the features in the database. The image analysis is performed in three steps. A location of six region of interest is followed by their segmentation and feature extraction. The features analysis results in retrieving the closest image match from the standard database. Based on currently analyzed image data in the hand atlas, the standard deviation of the assessment bone age does not exceed 1 yr of age.

Age Determination by Skeleton↗