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Recently, a development of the medical instrument using the vision information is brisk. Especially, extracting the 3-dimension information from 2-dimension image is the one of the major research topics. This paper proposes the method to measure tumor size by the 3-dimension information extraction, the triangulation using the extracted 3-dimension information and the camera geometry. To extract the...
This paper presents a method to estimate the signal strength of the functional near infrared spectroscopy (fNIRS) as parameters of orthogonalized form of general linear model (GLM). The idea is to convert the basis function (design matrix) or explanatory variables of a GLM into orthogonal functions using the usual Gram-Schmidt orthogo-nalization procedure. The coefficients associated with the orthogonal...
CAD (Computer Aided Diagnosis) system that has 3-D viewer function to display the DICOM (Digital Imaging and Communication in Medicine) image has been developed in recent years. Now, the function of CAD system for artificial implant to which development is advanced includes the removal of artifact in the input DICOM image, region extraction of bone, major vessel, and nerve and mounting of function...
Image segmentation of hematocyte is a practice of computer medical detection which is based on the medical characteristics of hematocyte, the Computer Graphics, and Image Segmentation. In this paper, we have proposed anew color components' exchanging method on different color spaces for image segmentation. First, extract the color components of the original image, then exchange the order of color...
Tongue diagnosis is a method to analyze disease by observing tongue, which composed of observing tongue proper and tongue coating. The separation of tongue coating and tongue proper is a premise to establish a system of automatic diagnosis by the feature of tongue image in traditional Chinese medicine, whose qualities affect on the performance of tongue diagnosis. In this paper, we present a novel...
In functional magnetic resonance imaging (fMRI) data, activated voxels are usually very small in number and are embedded in a mass of inactive voxels. For clustering analysis, this situation generates an ill-balanced data problem among different classes of voxels. In this paper we propose a novel method to overcome the ill-balanced data problem, by reducing the number of voxels to be processed by...
This paper presents a novel method for adaptive filtering of functional magnetic resonance imaging (fMRI) time-series. The method progressively reduces noise from the fMRI time courses based on selective spatial averaging of the underlying voxels. A new similarity measure is proposed to assign the weights of the averaging kernel. The performance of the proposed method is verified by its application...
Indirect immunofluorescence (IIF) with HEp-2 cells has been used to detect antinuclear auto-antibodies (ANA) for diagnosing systemic autoimmune diseases. The aim of this study is to develop an automatic scheme to identify the fluorescence pattern of HEp-2 cell in the IIF images. By using the previously proposed two-staged segmentation method, the similarity-based watershed algorithm with marker techniques...
This research aims at developing an optimal neural network based DSS, which is aimed at precise and reliable diagnosis of chronic active hepatitis (CAH) and cirrhosis (CRH). The principal component analysis neural network is designed scrupulously for classification of these diseases. The neural network is trained by eight quantified texture features, which were extracted from five different region...
This paper presents a new method of medical image registration for affinely deformed images using steerable wavelets. Mutual information based methods are often used in medical image registration due to their accuracy. Multiresolution image registration approach has a potential to speed up the computation of mutual information based methods. In this paper, use of steerable wavelets is proposed for...
In video-fluoroscopic swallowing assessment the time taken for the bolus material to transit the oral and pharyngeal regions is currently estimated by visual inspection. This paper presents an effective method for objectively approximating these timings by fitting a Gaussian surface to the first derivative of the intensity profiles along user defined anatomical boundaries. The profile characteristics...
Detection of brain tumors from MRI is a time consuming and error-prone task. This is due to the diversity in shape, size and appearance of the tumors. In this paper, we propose a clustering algorithm based on Particle Swarm Optimization (PSO). The algorithm finds the centroids of number of clusters, where each cluster groups together brain tumor patterns, obtained from MR Images. The results obtained...
To date, cancer of the uterine cervix is still a leading cause of cancer-related deaths in women in the world. Papanicolau smear test is a well-known screening method of detecting abnormalities in the uterine cervix cells. In Indonesia, Pap smear test is mostly still done conventionally. Due to the small number of skilled and experienced cytologists, the screening procedure becomes time consuming...
Artificial Neural Networks (ANN) is gaining significant importance for pattern recognition applications particularly in the medical field. A hybrid neural network such as Counter Propagation Neural Network (CPN) is highly desirable since it comprises the advantages of supervised and unsupervised training methodologies. Even though it guarantees high accuracy, the network is computationally non-feasible...
Artificial neural networks (ANN) and fuzzy systems are the widely preferred artificial intelligence techniques for biological computational applications. While ANN is less accurate than fuzzy logic systems, fuzzy theory needs expertise knowledge to guarantee high accuracy. Since both the methodologies possess certain advantages and disadvantages, it is primarily important to compare and contrast these...
Artificial Neural Networks (ANN) is currently a hot research area in medicine and it is believed that they will receive extensive application to biomedical systems in the next few years. Neural networks are ideal in recognizing diseases using scans since there is no need to provide a specific algorithm on how to identify the disease. This paper describes an algorithm to separate the lung tissue from...
In today's world, increasing life expectation have made the heart failures of important concern. For clinical diagnosis, parameters for the condition of heart are needed. Accurate and fast image segmentation algorithms are of paramount importance prior to the calculation of these parameters. An automatic method for segmenting the cardiac magnetic resonance (CMR) images is always desired to increase...
In this work, a hybrid approach to analyse optic disc and macula to characterise the normal and abnormal status of the retina are proposed. The retinas with normal and diabetic retinopathy (DR) images were used for this study. The fundus retinal images are subjected to ant colony optimization (ACO) based method to identify optic disc (OD) and Otsu method to further analyse the macula. Parameters such...
We present an adaptive smoothing scheme for denoising functional magnetic resonance imaging (fMRI) data using weighted average filtering. A novel metric is proposed that assigns the weights of the smoothing kernel on the basis of similarity of the voxels under the smoothing kernel with the voxel under consideration as well as a reference time course. Pearson's coefficient of correlation is used as...
Medical Diagnosis is the utmost need of an hour. Gestational Diabetics in women represents the second leading cause of yielding children born with birth defects. The ultrasound images are usually low in resolution making diagnosis difficult. Specialized tools are required to assist the medical experts to categorize and diagnose diseases to accuracy. If the anomalies in the ultrasound images are detected...
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