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 present the lumen coronary artery border detection using intravascular ultrasound (IVUS) images. The approach make used of texture analysis based on Binary Robust Independent Elementary Features (BRIEF) and Chi-square classification. This proposed method can detect the boundary and calculate the area within the lumen coronary artery border. This method was tested on thirty samples...
Segmentation is an important process especially in a Computer Aided Diagnosis (CADx) system. There are various methods of segmentation. A large majority of these involve a threshold based approach. For this study full HRCT Thorax scans from 10 normal patients were analysed. This study proposes a performance evaluation system for segmentation system. The performance evaluation uses five measures which...
In the field of neuropsychiatrie disorders, it is known that brain segmentation is important for both detection and diagnosis. The segmentation of the brain, which leads to the computation of brain volume proved to be vital in the detection of many brain pathology having Computed Tomography (CT) scan as the primary modality. Due to the fact that Fuzzy c-Means (FCM) proven to be robust, it is often...
Selamat Datang! (Welcome!) to the First International Conference on BioSignal Analysis, Processing and Systems (ICBAPS 2015). This conference is organized by Razak School of Engineering and Advanced Technology of Universiti Teknologi Malaysia with the collaboration of IEEE Malaysia Signal Processing Chapter as the technical cosponsor. ICBAPS 2015 attracted about 50 papers from 9 different countries...
In this paper we present an automated segmentation method to detect the boundary between adventitia and media on the cross sectional view of the artery of patients who have plaques. The problem encounter is that the boundaries of the adventitia, media, intima and lumen are embedded when plaques exist. Moreover, the artery disease has damaged the tissue layers. This paper proposed a method in segmenting...
Brain segmentation is important in the field of neuropsychiatric disorders. With Computed Tomography (CT) scan being the gold standard in brain scan, brain segmentation in CT images is also very important in the detection of many pathology related to the brain. Fuzzy c-Means (FCM) is a popular method in data clustering and also in image segmentation due to it being robust. Graph cut is a segmentation...
The success of eliminating the disease Mycobacterium Tuberculosis (MTB) depends on the detection capabilities of medical organizations. In Malaysia, the government hospitals perform the major part of this particular task. An important ingredient of the diagnostic process in government hospital is the visual interpretation of standard chest X-ray films. A previous study proposed an objective alternative;...
Radiologists are known to suffer from fatigue and drop in diagnostic accuracy due to large number of slices to read and long working hours. A computer aided diagnosis (CAD) system could help lighten the workload. Segmentation is the first step in a CAD system. This study aims to propose an accurate automatic segmentation. This study deals with High Resolution Computed Tomography (HRCT) scans of the...
The conventional chest radiograph remains a widely tool in the diagnosis of lung diseases even to the present day. Current methods or algorithms for disease detection focus on the discrimination between normal images and images with signs of disease involving chest radiograph. This paper proposed a novel algorithm to solve the difficult problem of discriminating two similar diseases, pulmonary tuberculosis...
High rsolution computed tomography (HRCT) thorax imaging is a trusted modality which is widely used in medical institutions to detect respiratory disease, in particular, interstitial lung disease (ILD) detection. Observing the enormous number of slices for single patient is time consuming and consequently may lead to human error. In order to overcome to this problem, developing computer aided diagnostic...
This paper presents a hybrid method of iris detection system based on edge detection and Hough Transform, with the help of skin segmentation in face detection algorithm, Golden Face Ratio and geometric definition. The algorithm starts with skin detection using Gaussian mixture model to find the bounding area of the face. Next, the facial area is used to mask the area for eye segmentation process....
This study attempted to discriminate three types of lung disease pair-wise, namely lobar pneumonia (PNEU), pulmonary tuberculosis (PTB) and lung cancer (LC) using chest radiograph. A modified principal component method applied to wavelet texture measures yielded feature vectors for the pair-wise statistical discrimination procedure. The combination of mean of energy and maximum value texture measures...
This study's objective is to execute successful segmentation of the lung anatomy of HRCT of patients who have ILD and evaluate the segmentation performance. Initial segmentation process involved Otsu grey level thresholding and morphological filtering. Some of the problems encountered were the appearance of connected lungs because the left lung and right lung were very close to each other, and heavily...
Face detection for low quality images and different face positions is a very challenging task. This paper presents a hybrid method for face detection to these problems. The algorithm starts with image resizing process followed by the Gaussian Mixture Model to calculate the skin likelihood value of pixel in an image. Then, the skin regions are extracted from the background with a proper threshold value...
The appearance of the infected zone on the digital chest X-ray image for pulmonary tuberculosis (PTB) does not conform to standard shape, size or configuration. This study uses phase congruency (PC(x)) values to gather information from transition of adjacent pixel values that may be used as features to represent known disease type. The feature vector consisting of the average, variance, coefficient...
The task of making inferences from a digital image frequently revolves around the ability to use multi-dimensional data or feature vectors optimally. This paper proposes directions in the handling of feature vectors with multivariate statistical methods with illustrations from three areas of applications. Experience shows that wherever possible, the lowest dimension of the feature vector is preferred...
Correlation generally shows the relationship between variables. A judicious use of this relationship may yield a measure of performance for a given algorithm. In this study the correlation measure RP2 derived from the Unreplicated Linear Functional relationship (ULFR) model will be shown to be a useful measure of performance in selected procedure or algorithm for a particular image registration method,...
A series of chest radiograph images will be compared for purposes of monitoring effect of treatment on a given Mycobacterium Tuberculosis (MTB) patient. A subset of the first image corresponding to the patients first visit to the clinic will be selected as being representative of the infected areas. The corresponding subset from the second image (second visit) will be similarly obtained, and then...
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.