Application of the Teager-Kaiser Energy Operator in an autonomous burst detector to create onset and offset profiles of forearm muscles during reach-to-grasp movements.

PURPOSE: The primary aim of this study is to investigate the potential benefit of the Teager-Kaiser Energy Operator (TKEO) as data pre-processor, in an autonomous burst detection method to classify electromyographic signals of the (fore)arm and hand. For this purpose, optimal settings of the burst detector, leading to minimal detection errors, need to be known. Additionally, the burst detector is applied to real muscle activity recorded in healthy adults performing reach-to-grasp movements. METHODS: The burst detector was based on the Approximated Generalized Likelihood Ratio (AGLR). Simulations with synthesized electromyographic (EMG) traces with known onset and offset times, yielded optimal settings for AGLR parameters "window width" and "threshold value" that minimized detection errors. Next, comparative simulations were done with and without TKEO data pre-processing. Correct working of the burst detector was verified by applying it to real surface EMG signals obtained from arm and hand muscles involved in a submaximal reach-to-grasp task, performed by healthy adults. RESULTS: Minimal detection errors were found with a window width of 100 ms and a detection threshold of 15. Inclusion of the TKEO contributed significantly to a reduction of detection errors. Application of the autonomous burst detector to real data was feasible. CONCLUSIONS: The burst detector was able to classify muscle activation and create Muscle Onset Offset Profiles (MOOPs) autonomously from real EMG data, which allows objective comparison of MOOPs obtained from movement tasks performed in different conditions or from different populations. The TKEO contributed to improved performance and robustness of the burst detector.

IVEU: IT-based collection and reporting of radiological examination parameters.

In Germany, each site using ionising radiation in human medicine is assigned to a competent medical authority (CMA) for quality assurance. Duties of these CMAs are, e.g. the inspection of medical aspects of the use of X-rays and nuclear medicine at the sites as well as technical quality assurance of X-ray devices. The CMAs themselves have to report the collected exposure values to the ministries and the Federal Office for Radiation Protection. The IVEU (IT-gestütztes Verfahren zur Erfassung von Untersuchungsparametern) Software Framework assists CMAs and radiological departments in collecting and analysing data provided in DICOM headers.

Automatic computed tomography patient dose calculation using DICOM header metadata.

The present work describes a method that calculates the patient dose values in computed tomography (CT) based on metadata contained in DICOM images in support of patient dose studies. The DICOM metadata is preprocessed to extract necessary calculation parameters. Vendor-specific DICOM header information is harmonized using vendor translation tables and unavailable DICOM tags can be completed with a graphical user interface. CT-Expo, an MS Excel application for calculating the radiation dose, is used to calculate the patient doses. All relevant data and calculation results are stored for further analysis in a relational database. Final results are compiled by utilizing data mining tools. This solution was successfully used for the 2009 CT dose study in Luxembourg. National diagnostic reference levels for standard examinations were calculated based on each of the countries' hospitals. The benefits using this new automatic system saved time as well as resources during the data acquisition and the evaluation when compared with earlier questionnaire-based surveys.

Optimage central organised image quality control including statistics and reporting.

Quality control of medical imaging systems is performed using dedicated phantoms. As the imaging systems are more and more digital, adequate image processing methods might help to save evaluation time and to receive objective results. The developed software package OPTIMAGE is focusing on this with a central approach: On one hand, OPTIMAGE provides a framework, which includes functions like database integration, DICOM data sources, multilingual user interface and image processing functionality. On the other hand, the test methods are implemented using modules which are able to process the images automatically for the common imaging systems. The integration of statistics and reporting into this environment is paramount: This is the only way to provide these functions in an interactive, user-friendly way. These features enable the users to discover degradation in performance quickly and document performed measurements easily.