A low-cost sensor platform (MORES Sensor) was combined with a microcontroller to build up an embedded solution
which e.g. allows for a small hand-held Color Estimation System for blind people. The color sensor used here measures
the intensity response of a surface caused by radiation with a specific wavelength in the range of visible light. This
radiation is realized by means of three LEDs, red, green, and blue, so that the response intensity values create an R'G'B'
color space, which differs from the standardized RGB color space due to the wavelengths of the LEDs. By adjusting the
measured response of the LEDs to the known spectral response of the individual color panels of the Macbeth Color
Checker Chart (MCCC) a corresponding set of coordinates can be constructed for this particular R'G'B' color space.
Owing to this approach, it is possible to obtain reasonable color classification results, which can be compared to those of
far more complex and expensive systems. The verification of the results was done by using the standardized MCCC
together with commercial vision solutions (RGB camera in combination with PC software). Moreover, some comparison
tests also prove the practicality of the here described low-cost color sensor solution.
Quantification of vessel diameters of artherosclerotic or congenital stenosis is very important for the diagnosis of vascular diseases. The aorta extraction and cross-section calculation is a software-based application that offers a three-dimensional, platform-independent, colorized visualization of the extracted aorta with augmented reality information of MRT or CT datasets. This project is based on different types of specialized image processing algorithms, dynamical particle filtering and complex mathematical equations. From this three-dimensional model a calculation of minimal cross sections is performed. In user specified distances, the aorta is cut in differently defined directions which are created through vectors with varying length. The extracted aorta and the derived minimal cross-sections are then rendered with the marching cube algorithm and represented together in a three-dimensional virtual reality with a very high degree of immersion. The aim of this study was to develop an imaging software that delivers cardiologists the possibility of (i) furnishing fast vascular diagnosis, (ii) getting precise diameter information, (iii) being able to process exact, local stenosis detection (iv) having permanent data storing and easy access to former datasets, and (v) reliable documentation of results in form of tables and graphical printouts.
Rheumatoid Arthritis (RA) is a common systemic disease predominantly involving the joints. Precise diagnosis and follow-up therapy requires objective quantification. For this purpose, radiological analyses using standardized scoring systems are considered to be the most appropriate method. The aim of our study is to develop a semi-automatic image analysis software, especially applicable for scoring of joints in rheumatic disorders. The X-Ray RheumaCoach software delivers various scoring systems (Larsen-Score and Ratingen-Rau-Score) which can be applied by the scorer. In addition to the qualitative assessment of joints performed by the radiologist, a semi-automatic image analysis for joint detection and measurements of bone diameters and swollen tissue supports the image assessment process. More than 3000 radiographs from hands and feet of more than 200 RA patients were collected, analyzed, and statistically evaluated. Radiographs were quantified using conventional paper-based Larsen score and the X-Ray RheumaCoach software. The use of the software shortened the scoring time by about 25 percent and reduced the rate of erroneous scorings in all our studies. Compared to paper-based scoring methods, the X-Ray RheumaCoach software offers several advantages: (i) Structured data analysis and input that minimizes variance by standardization, (ii) faster and more precise calculation of sum scores and indices, (iii) permanent data storing and fast access to the software’s database, (iv) the possibility of cross-calculation to other scores, (v) semi-automatic assessment of images, and (vii) reliable documentation of results in the form of graphical printouts.