Mohammadreza Yadollahi

The MS kinect image and depth sensors use for gait features detection

Movement disorders, problems with motion and gait stability related to aging form a very intensively studied research area. The paper presents a contribution to these topics through the use of data acquired by motion sensors and namely image and depth sensors of the MS Kinect. While video sequences obtained by complex camera systems can be used for the precise gait features evaluation, it is possible to use much cheaper devices for diagnostic purposes accurate enough in many cases. The experimental part of the study presents video sequences and depth sensors data acquisition for 18 individuals with the Parkinsons disease and 18 healthy age-matched controls using the proposed graphical user interface in the clinical environment. Results presented include the estimation of gait features to distinguish gait disorders and to classify individuals in the early stage of possible serious diseases. The accuracy achieved was higher then 90 % for given sets of individuals.

The use of combined illumination in segmentation of orthodontic bodies

This paper presents new methods of orthodontic body segmentation using digital records of their plaster cast models under different types of illumination. Selected light conditions are used for the data acquisition to provide more clearly defined contours of the image components. The preliminary stage of the data processing uses the circular Hough transform, digital de-noising, and a separation of the orthodontic objects from their backgrounds employing Otsu’s thresholding method. The region-growing method using multiple seed points in a convex hull is then applied. The proposed general method identifies the common boundary of two neighboring and overlapping orthodontic objects with results enabling the efficient segmentation of digital data and their analysis through the computer network.

Evaluation of dental morphometrics during the orthodontic treatment

BackgroundDiagnostic orthodontic and prosthetic procedures commence with an initial examination, during which a number of individual findings on occlusion or malocclusion are clarified. Nowadays we try to replace standard plaster casts by scanned objects and digital models.MethodGeometrically calibrated images aid in the comparison of several different steps of the treatment and show the variation of selected features belonging to individual biomedical objects. The methods used are based on geometric morphometrics, making a new approach to the evaluation of the variability of features. The study presents two different methods of measurement and shows their accuracy and reliability.ResultsThe experimental part of the present paper is devoted to the analysis of the dental arch objects of 24 patients before and after the treatment using the distances between the canines and premolars as the features important for diagnostic purposes. Our work proved the advantage of measuring digitalized orthodontic models over manual measuring of plaster casts, with statistically significant results and accuracy sufficient for dental practice.ConclusionA new method of computer imaging and measurements of a dental stone cast provides information with the precision required for orthodontic treatment. The results obtained point to the reduction in the variance of the distances between the premolars and canines during the treatment, with a regression coefficient RC=0.7 and confidence intervals close enough for dental practice. The ratio of these distances pointed to the nearly constant value of this measure close to 0.84 for the given set of 24 individuals.

Separation of overlapping dental arch objects using digital records of illuminated plaster casts

BackgroundPlaster casts of individual patients are important for orthodontic specialists during the treatment process and their analysis is still a standard diagnostical tool. But the growing capabilities of information technology enable their replacement by digital models obtained by complex scanning systems.MethodThis paper presents the possibility of using a digital camera as a simple instrument to obtain the set of digital images for analysis and evaluation of the treatment using appropriate mathematical tools of image processing. The methods studied in this paper include the segmentation of overlapping dental bodies and the use of different illumination sources to increase the reliability of the separation process. The circular Hough transform, region growing with multiple seed points, and the convex hull detection method are applied to the segmentation of orthodontic plaster cast images to identify dental arch objects and their sizes.ResultsThe proposed algorithm presents the methodology of improving the accuracy of segmentation of dental arch components using combined illumination sources. Dental arch parameters and distances between the canines and premolars for different segmentation methods were used as a measure to compare the results obtained.Conclusion A new method of segmentation of overlapping dental arch components using digital records of illuminated plaster casts provides information with the precision required for orthodontic treatment. The distance between corresponding teeth was evaluated with a mean error of 1.38% and the Dice similarity coefficient of the evaluated dental bodies boundaries reached 0.9436 with a false positive rate

Sleep scoring using polysomnography data features

FPR=0.0381

Separation of overlapping dental objects using normal vectors to image region boundaries

FPR=0.0381 and false negative rate

Remote physiological and GPS data processing in evaluation of physical activities

FNR=0.0728