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Many diseases affect the knee joint, such as Chondromalica Pattelle (CP), which is the most bearing joint in the body. X-ray, MRI and arthroscopy are currently used for screening knee joint diseases. However, some of these techniques may be costly, dangerous as well as some of them being poor in functional resolution. On the other hand, researchers have shown the existence of variation in Vibroarthrography...
The differential diagnosis of proliferative breast lesions, benign usual ductal hyperplasia (UDH) versus malignant ductal carcinoma in situ (DCIS) is challenging. This involves a pathologist examining histopathologic sections of a biopsy using a light microscope, evaluating tissue structures for their architecture or size, and assessing individual cell nuclei for their morphology. Imposing diagnostic...
Paleness or pallor is a manifestation of blood loss or low hemoglobin concentrations in the human blood that can be caused by pathologies such as anemia. This work presents the first automated screening system that utilizes pallor site images, segments, and extracts color and intensity-based features for multi-class classification of patients with high pallor due to anemia-like pathologies, normal...
Magnetic resonance imaging (MRI) is a kind of imaging modality, which offers clearer images of soft tissues than computed tomography (CT). It is especially suitable for brain disease detection. It is beneficial to detect diseases automatically and accurately. We proposed a pathological brain detection method based on brain MR images and online sequential extreme learning machine. First, seven wavelet...
We consider a task of classifying normal and pathological brain networks. These networks (called connectomes) represent macroscale connections between predefined brain regions, hence, the nodes of connectomes are uniquely labeled and the set of labels (brain regions) is the same across different brains. We make use of this property and hypothesize that connectomes obtained from normal and pathological...
The number of woman with cervical cancer in Indonesia is getting higher. Indonesia becomes the country with the highest number of women with cervical cancer in the world. Cervical cancer became the highest cause of cancer deaths in women globally. There has been a lot of research using data mining techniques with variety of different data mining models that can be used for analyzing cervical cancer...
In our study we present a method to identity pathological voices using Support Vector Machines (SVM). Speech signals were sampled from the sustained vowel /a/ pronounced by 160 subjects (80 female and 80 male), including 80 speakers (40 women and 40 men) suffered from various dysphonias (such as acute laryngitis, adductor spasmodic, vocal fatigue, vocal tremor, vocal fold edema, laryngeal paralysis…),...
Parkinson, is the second most common neurodegenerative disease after Alzheimer and no absolute cure has yet been found for it; however, the progression rate can be lowered with early diagnosis. Minor voice disorders are the first symptoms of this disease and they appear in almost 90% of the patients. The aim of this article to find the features that can create more meaningful difference between healthy...
The Active Anterior Rhinomanometry method for an objective assessment of nasal breath is carried out. The preprocessing's methods for rhinomanometric data were analyzed. It was proposed to use the method of fuzzy approximation based on F-transform for preprocessing of rhinomanometric signals.
In this work, sub anatomic regions of brain are studied using diffusion tensor images. Images of normal controls (NC) and Alzheimer disease (AD) subjects were obtained from ADNI database. Volume of four regions (Thalamus, Posterior cingulate, Temporal lobe and Hypothalamus) were estimated by implementing voxel analysis and atlas based approach. All the regions showed a reduction in volume. The variation...
Traumatic brain injury (TBI) is a major health problem and the most common cause of permanent disability in people under the age of 40 years. In this paper, we present a fully automatic framework for the analysis of acute computed tomography (CT) images in TBI. Different pathologies common in TBI are quantified and all the information is combined for clinical outcome prediction in individual patients...
Ultrasound (US) imaging is more popular as a diagnostic tool than magnetic resonance imaging (MRI) and computerized tomography (CT) because it is inexpensive and easy to use. Most lymph nodes (LN) tend to have various internal echogenicities in the sonogram, which makes a definite diagnosis difficult. If the characteristic echogenicities for the major components of the lymph node can be identified,...
The aim of the research is to investigate the connection that may exist between the changes of the pronunciation of the /v/ and /f/ French fricative consonants and the dentistry pathologies. We perform this analysis at the formantic level, focusing on the statistical features like the median values of the F1-F4 formants, the first and third quartiles of the F1 formant, and on the presence or absence...
The high order pattern discovery algorithm is applied to classify schizophrenia and health's EEG signals. Samples of 780 schizophrenia and health EEG pieces are classified. The result shows that the classification accuracy can achieve 90% in 6-order. The 6-orders are associated with frontal polar, temporal and occipital regions.
Research in time-frequency distributions (TFDs) is limited in terms of their use of the available spatial domains and in their target applications. Most of the work up till now has been concentrated mainly on the t-f domain space. This work presents a detailed study about the ambiguity domain (AD), their resemblance in the t-f space and the significance of using such a representation. Further, a novel...
The proper application of statistics, machine learning, and data-mining techniques in routine clinical diagnostics to classify diseases using their genetic expression profile is still a challenge. One critical issue is the overall inability of most state-of-the-art classifiers to identify out-of-class samples, i.e., samples that do not belong to any of the available classes. This paper shows a possible...
In this paper, we are proposing a novel automated method to recognize centroblast (CB) cells from non-centroblast (non-CB) cells for computer-assisted evaluation of follicular lymphoma tissue samples. The method is based on training and testing of a quadratic discriminant analysis (QDA) classifier. The novel aspects of this method are the identification of the CB object with prior information, and...
Advances in medical imaging techniques and devices has resulted in increased use of imaging in monitoring disease progression in patients. However, extracting decision-enabling information from the resulting longitudinal multi-modal image sets poses a challenge. Radiologists often have to manually identify and quantify certain regions of interest in the longitudinal image sets, which bear upon the...
This work presents an infant cry automatic recognizer development, with the objective of classifying two kinds of infant cries, normal and pathological, from recently born babies. Extraction of acoustic features is used such as MFCC (Mel Frequency Cepstral Coefficients), obtained from Infant Cry Units sound waves, and a genetic feature selection system combined with a feed forward input delay neural...
The present paper proposes the use of a basic element for the infant cry analysis: the cry unit. In order to display the real possibility of the cry unit for the detection of pathological features (based on Hypoxia) in newborns, a novel combined treatment of the cry signal was implemented using an evolutionary-neural system. For that purpose the cry signal was segmented into cry units, the MFCC were...
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