Amir Babaoghli; Hadi Soltanizadeh
Volume 13, Issue 3 , October 2019, , Pages 235-246
Abstract
Diseases associated with the retina and macula of the eye, causing permanent loss of vision or a great deal of loss of vision in people, leads to a decrease in the quality of life and a lot of problems in daily life. For this reason, the timely and correct identification of these diseases and disorders ...
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Diseases associated with the retina and macula of the eye, causing permanent loss of vision or a great deal of loss of vision in people, leads to a decrease in the quality of life and a lot of problems in daily life. For this reason, the timely and correct identification of these diseases and disorders has become important. The optical coherence tomography imaging method provides high precision in imaging and good information about the depth of the retina. This imaging technique is a great help in the accurate identification of macular-related diseases. Age-related macular degeneration is one of the most common retinal diseases. The purpose of this study is to design and implement a system that is reliable, fast and can detect the age-related macular degeneration by using optical coherence tomography image processing accurately and quickly. In these studies, histograms of orientational gradients and principal component analysis for extraction of features and AdaBoost ensemble classification method have been used to classify the data. The database used includes 269 patients and 115 healthy people. All three indicators of accuracy, sensitivity and specificity of the implemented system were measured at 100%.
Biomedical Image Processing / Medical Image Processing
maryam bagheri baghan; vahid azadzadeh; ali mohammad latif
Volume 10, Issue 2 , August 2016, , Pages 137-148
Abstract
It is a common approach to diagnose a disease based on the tongue in Traditional Chinese Medicine. In this paper, a noninvasive imaging of tongue whose surface papilla change in diabetics is used to detect the disease. The required images have been provided by Parsian specialized clinic of Mashhad. In ...
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It is a common approach to diagnose a disease based on the tongue in Traditional Chinese Medicine. In this paper, a noninvasive imaging of tongue whose surface papilla change in diabetics is used to detect the disease. The required images have been provided by Parsian specialized clinic of Mashhad. In the sampling procedure, the diabetics, healthy individuals and those suspected of diabetes with both sexes and different age groups were considered. After imaging, tongue region was segmented based on two active contour models; then extended local binary patterns features, statistical features of the tongue texture, Color Moments in different color spaces were extracted from the segmented region. After feature extraction, diabetics, healthy and suspected of diabetes were detected using extreme learning machine classification. The proposed method obtained a precision of 97.7% for the current database. Experimental results show the efficiency and responding time of the proposed method compared to other noninvasive methods.
Biomedical Image Processing / Medical Image Processing
Alireza Rahimpour; Abbas Nasiraei Moghaddam
Volume 6, Issue 3 , June 2012, , Pages 195-205
Abstract
Nowadays eye gaze tracking has wide range of applications in human computer interaction. One of these applications is using trajectory of eye gaze instead of foot or hand for disabled people to execute some commands. Various methods have been proposed, some of this methods can successfully track the ...
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Nowadays eye gaze tracking has wide range of applications in human computer interaction. One of these applications is using trajectory of eye gaze instead of foot or hand for disabled people to execute some commands. Various methods have been proposed, some of this methods can successfully track the eye gaze. However, they always require specific circumstances, training or are not capable of real-time performance. In this paper, we proposed a framework to track eye gaze in real-time by using a simple and low cost webcam mounted on ordinary laptops. This process widely exploits the weighted normalized correlation function in an adaptive template matching approach. The implemented system tracks the face and also extracts some eye features such as iris position, eye corners and sclera region in eyes, in real time. These features are used in eye gaze estimation. Also the influence of illumination changes, background alterations, different faces and face movements is minimized as much as possible. The implemented gaze tracking system is able to control the motions of mouse cursor and click on an onscreen keyboard in real time.
Biomedical Image Processing / Medical Image Processing
Nader Riahi Alam; Reza Aghaeizade Zoroofi; Masoume Giti; Arian Deldari; Alireza Ahmadian
Volume 1, Issue 3 , June 2007, , Pages 157-165
Abstract
In this study, the need of a CAD system and its capabilities has been investigated and then a sample program for a mammographic CAD system proper to Iranian tropical patients was designed. In the first step, the analog mammographic images were digitized by 56 and 112 mm spatial resolution and then were ...
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In this study, the need of a CAD system and its capabilities has been investigated and then a sample program for a mammographic CAD system proper to Iranian tropical patients was designed. In the first step, the analog mammographic images were digitized by 56 and 112 mm spatial resolution and then were processed by the designed sample program. Analysis and technical details for designing and implementing the program included for following steps: The capability of the program image displayer consisting of viewing four mammographic images from four breast views (RCC, RMLO, LCC, LMLO) in one window, determining breast region by background removing and other conventional preprocessing application tools; Software processing tools including theresholding, histogram, ROI determination; Patient information fields such as clinical information, conventional reporting section as used in radiological department in Iran; Computer-aided diagnostic section including proper diagnostic processing algorithm to automatic detection of breast abnormality. For instance the application of wavelet and fuzzy logic for detecting malignant clusters of microcalcification. The introduced mammographic CAD system can provide the collection, organizing and the availability of the patient local information. Therefore by using the prepared database the evaluation of the sensitivity and specifity of the detecting algorithm for comparison of different research methods would be possible.
Biomedical Image Processing / Medical Image Processing
Hadi Jafariani; Hamid Abrishami Moghaddam; Mohammad Shahram Moein
Volume 1, Issue 4 , June 2007, , Pages 311-318
Abstract
One of the most accurate techniques for human identification is based on the uniqueness of the retinal blood vessels pattern. In this paper, we present a new approach for human identification using retina image. This approach is insensitive to rotation, scaling and translation. The Fourier-Mellin transform ...
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One of the most accurate techniques for human identification is based on the uniqueness of the retinal blood vessels pattern. In this paper, we present a new approach for human identification using retina image. This approach is insensitive to rotation, scaling and translation. The Fourier-Mellin transform coefficients and moments of the retinal image were used to extract the suitable features. To compensate the rotational effects caused by different relative positions of the retina scanner with respect to the eye, a rotation compensator was designed. For retinal image interpretation, the optic disc location was considered as a fixed and reference point. For its localization, the Haar wavelet and the Snakes model were used. The experimental results demonstrated an error rate close to zero for the proposed method.
Biomedical Image Processing / Medical Image Processing
Ladan Amini; Hamid Soltanian Zadeh; Caro Lucas; Masoume Giti
Volume -2, Issue 1 , July 2005, , Pages 17-34
Abstract
Based on a discrete dynamic contour model, a method for segmentation of brain structures like thalamus and red nucleus from magnetic resonance images (MRI) is developed. A new method for solving common problems in extracting the discontinuous boundary of a structure from a low contrast image is presented. ...
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Based on a discrete dynamic contour model, a method for segmentation of brain structures like thalamus and red nucleus from magnetic resonance images (MRI) is developed. A new method for solving common problems in extracting the discontinuous boundary of a structure from a low contrast image is presented. External and internal forces deform the dynamic contour model. Internal forces are obtained from local geometry of the contour, which consist of vertices and edges, connecting adjacent vertices. The image data and desired image features such as image energy are utilized to obtain external forces. The problem of low contrast image data and unclear edges in the image energy is overcome by the proposed algorithm that uses several methods like thresholding, unsupervised clustering methods such as fuzzy C-means (FCM), edge-finding filters like Prewitt, and morphological operations. We also present a method for generating an initial contour for the model from the image data automatically. Evaluation and validation of the methods are conducted by comparing radiologist and automatic segmentation results. The average of the similarity between segmentation results is 0.8 for the left and right thalami indicating excellent performance of the new method. Additional noise and intensity inhomogeneity changed the evaluation results slightly illustrating the robustness of the proposed method to the image noise and intensity inhomogeneity.
Biomedical Image Processing / Medical Image Processing
Hamid Abrishami Moghaddam; Alireza Sheikh Hasani; Abbas Mostafa; Masoume Giti; Parviz Abdolmaleki
Volume -1, Issue 2 , June 2005, , Pages 117-128
Abstract
This paper presents a CAD system for detection and diagnosis of microcalcification clusters in mammograms. The proposed algorithm is composed of three main stages. In the first stage, the image pixels are examined for corresponding to individual microcalcification objects. For this purpose, the wavelet ...
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This paper presents a CAD system for detection and diagnosis of microcalcification clusters in mammograms. The proposed algorithm is composed of three main stages. In the first stage, the image pixels are examined for corresponding to individual microcalcification objects. For this purpose, the wavelet transform of the image is computed. Then two wavelet coefficients as well as two statistical features are used with a neural network for a primary classification of the image pixels. In the second stage, some noisy pixels extracted by the first step are eliminated. Then 18 features defined for each microcalcification are used with a nonlinear classifier for accurate detection of microcalcifications. For training of this classifier we used 16 regions from a database containing 379 microcalcifications. Finally, in the third stage five features defined for each microcalcification cluster with a neural network are used to recognize malignant microcalcification clusters. For training of this network, 22 clusters including 8 malignant and 14 benign cases were used. The performance of the algorithm was evaluated using a separate image set composed of 22 clusters including 10 malignant and 12 benign cases. Using these tests images and the threshold value of 0.45, the sensitivity of the algorithm was 100% and its specificity was 91.6%.
