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.
Implementation of a neuro-fuzzy segmentation process of the MRI data is presented in this study to detect various tissues like white matter, gray matter, csf and tumor. The advantage of hierarchical self organizing map and fuzzy c means algorithms are used to classify the image layer by layer. The lowest level weight vector is achieved by the abstraction level. We have also achieved a higher value...
The progress of medical imaging technologies, from X-ray radiography, ultrasonic graph to modern age's Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) scan has helped the advance of the medical technology as well as the improvement of medical care quality all over the world. It is essential to promote our own medical imaging technologies so as to reduce the future overall medical expense...
Image Segmentation is an important and challenging factor in the medical image segmentation. This paper describes segmentation method consisting of two phases. In the first phase, the MRI brain image is acquired from patients database, In that film artifact and noise are removed. After that Hierarchical Self Organizing Map (HSOM) is applied for image segmentation. The HSOM is the extension of the...
This study focuses on segmentation and validation of brain MR images. Artificial neural network (ANN) has been applied to obtain the targeted segments from these images. In preprocessing step for avoiding the chances of misclassification during training of ANN, the unwanted skull tissues were removed by employing active contour modeling (ACM). The removal of these tissues leaves an image containing...
Automatic Segmentation of brain MRI is used as a diagnostic tool in neuro medicine. Abnormal growth of brain tissues can be detected. Changes in volumetric growth of brain tissues such as white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) can help in the early detection of neural disorders like epilepsy, Alzhemeirpsilas disease etc. Automatic segmentation of brain is a challenging problem...
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.