Automatic Recognition and Classification of Cerebral Microemboli in Ultrasound Images
نویسندگان
چکیده
The aim of this work was the definition of a method devoted to the automated recognition of different composition of cerebral microemboli. The developed diagnostic procedure made use of a feature-based analysis of ultrasonographic images containing the characteristic microembolic signals. The images were acquired with a transcranial Doppler and classified using a hierarchical neural network. The proposed procedure was tested on clinical cases selected by expert neurologists for their relevance, and experimental results showed its reliability. Received October 25, 2004
منابع مشابه
Automatic classification of Non-alcoholic fatty liver using texture features from ultrasound images
Background: Accurate and early detection of non-alcoholic fatty liver, which is a major cause of chronic diseases is very important and is vital to prevent the complications associated with this disease. Ultrasound of the liver is the most common and widely performed method of diagnosing fatty liver. However, due to the low quality of ultrasound images, the need for an automatic and intelligent...
متن کاملAutomatic Classification of Benign And Malignant Liver Tumors In Ultrasound Images
Introduction: Differentiation of benign and malignant liver tumors is very important for finding appropriate treatment procedure. Human eyes sometime are not able to diagnose the type of liver tumor. Texture analysis is considered as a suitable method to increase the diagnostic power of medical images. In this study texture analysis is employed in order to classification of ben...
متن کاملAutomatic Face Recognition via Local Directional Patterns
Automatic facial recognition has many potential applications in different areas of humancomputer interaction. However, they are not yet fully realized due to the lack of an effectivefacial feature descriptor. In this paper, we present a new appearance based feature descriptor,the local directional pattern (LDP), to represent facial geometry and analyze its performance inrecognition. An LDP feat...
متن کاملOn the use of Textural Features and Neural Networks for Leaf Recognition
for recognizing various types of plants, so automatic image recognition algorithms can extract to classify plant species and apply these features. Fast and accurate recognition of plants can have a significant impact on biodiversity management and increasing the effectiveness of the studies in this regard. These automatic methods have involved the development of recognition techniques and digi...
متن کاملDetection and Classification of Breast Cancer in Mammography Images Using Pattern Recognition Methods
Introduction: In this paper, a method is presented to classify the breast cancer masses according to new geometric features. Methods: After obtaining digital breast mammogram images from the digital database for screening mammography (DDSM), image preprocessing was performed. Then, by using image processing methods, an algorithm was developed for automatic extracting of masses from other norma...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2005