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Populations of healthy older individuals are often highly heterogeneous, as prevalence of various underlying pathologies increases with age. Finding coherent groups of normal older adults may allow to identify subpopulations that are at risk of developing Alzheimer's disease (AD). In this paper, we propose an approach that utilizes longitudinal magnetic resonance imaging (MRI) data to obtain natural...
Wireless Capsule Endoscopy (WCE) is a state-of-the-art technology to examine the entire gastrointestinal tract. Its main disadvantage is long review time for physicians to diagnose diseases, as it will produce over 55,000 frames per patient for one examination. In this paper we propose a novel strategy to segment WCE video clips based on abnormality. The new scheme is based on a non-parametric corner...
This paper describes a method using image processing and genetic algorithm-neural network (GA-NN) for automated Mycobacterium tuberculosis detection in tissues. The proposed method can be used to assist pathologists in tuberculosis (TB) diagnosis from tissue sections and replace the conventional manual screening process, which is time-consuming and labour-intensive. The approach consists of image...
In order to discriminate normal and abnormal heart sounds (HSs) accurately and effectively, a new method for clinical diagnosis of the heart valve diseases is proposed. The method is composed of three stages. The first stage is the preprocessing stage. During the pre-processing stage, the improved wavelet threshold shrinkage denoising algorithm is used for the noise reduction of the measured HSs....
This paper presents a novel hybrid approach based on clustering technique (CT) and least square support vector machine (LS-SVM) denoted as CT-LS-SVM for classifying two-class EEG signals. The study aims to extract representative features from the original EEG data through the CT method and then to classify two-class EEG signals by the LS-SVM using these features as inputs. In order to test the effectiveness...
There is need to quantify the dental plaque in order to keep fit and prevent occurrence from vital diseases. Dental plaque quantification is very crucial to patients, dentists as well as researchers. This paper presented a method to automatically quantifying the dental plaque in digital tooth images using mean shift. The proposed approach was applied to a clinical database consisting of 30 objects...
Pulmonary radiographs are essential tools to the evaluation and diagnosis of suspected infections of the lower respiratory system. Interpretation of a radiograph in the clinical context is a valuable diagnostic adjunct to the selection and the management of a specific clinical protocol for therapy. The key element in the proper diagnosis of a bacterial pulmonary infection is the analysis of the radiographic...
We present the application of an Amplitude-Modulation Frequency-Modulation (AM-FM) method for extracting potentially relevant features towards the classification of diseased retinas from healthy retinas. In terms of AM-FM features, we use histograms of the instantaneous amplitude, the angle of the instantaneous frequency and the magnitude of the instantaneous frequency extracted over different frequency...
In this paper, the clustering validation of spinal deformity classification by principal component analysis is introduced for the visualization of high dimensional patterns of the scoliosis spinal deformity with their reduced two-dimensional clustering properties. King spinal deformity classification system was used for PCA cluster implementation. The dataset used for this study had 25 spinal deformity...
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