The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, we propose an improved model, called three-dimensional (3-D) level set method, for active contours to detect maxillary sinuses in cone beam computed tomography(CBCT) images. This method is based on the techniques of two-dimensional(2-D) level set method and active contour without edges (or Chan-Vese) method. This model can detect the maxillary sinus correctly not only in normal cases,...
Eye tracking is widely useful in several fields especially in medical field to help human diagnosis and treatment. The proposed of this study is to develop eye tracking system using intensity measurement algorithm and apply into ophthalmic operating microscope. The proposed method has been proved to be accurate, reliable, and stable.
A revised group method of data handling (GMDH)-type neural network algorithm for medical image recognition is proposed and is applied to 3-dimensional medical image analysis of the heart. The revised GMDH-type neural network algorithm has a feedback loop and can identify the characteristics of the medical images accurately using feedback loop calculations. In this algorithm, the polynomial type and...
The feedback group method of data handling (GMDH)-type neural network algorithm proposed in this paper is applied to 3-dimensional medical image recognition of the brain. The neural network architecture fitting the complexity of the medical images is automatically organized so as to minimize the prediction error criterion defined as Akaikepsilas information criterion (AIC) or prediction sum of squares...
In this study, three dimensional medical images of the lungs and brain are recognized and extracted by artificial neural networks. The neural networks used in this paper are the conventional sigmoid function neural network trained using back propagation (BP) algorithm and radial basis function (RBF) neural network. We compared the recognition results of these neural networks and determine which neural...
A radial basis function (RBF) group method of data handling (GMDH)-type neural network algorithm proposed in this paper is applied to the medical image recognition of abdominal X-ray CT images. The optimum neural network architecture for the medical image recognition is automatically organized using RBF GMDH-type neural network algorithm and the regions of abdominal organs such as the liver, stomach...
MR compatible apparatus is essential to design new tasks for fMRI study. This paper described the development of an MR compatible manipulandum actuated by the ultrasonic motors, which was able to work within MRI scanner and to perform fMRI task continuously during finger movements. The prototype of manipulandum was able to produce two discriminable force fields: position dependent and velocity dependent...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.